Вакансии humanoid: работа в IT и digital

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role

We're hiring a VLA Pre-training Engineer to join our Autonomy team based in London. In this role you will you will work on all aspects of training capable policies, be it pre-training of a base model on a diverse multi-embodiment corpus of trajectories, fine-tuning a policy to perform a specific task well, curating data collection processes or exploring productive ways to generate and use synthetic data. This is primarily a deep learning-focused role, so we are looking for experience solving real problems using modern neural networks, while experience in robotics isn’t strictly required. However if you don’t have such experience, be prepared that you’d need to familiarize yourself with a new domain quickly.

What You'll Do

• Post-train policies via behaviour cloning and RL; own the full loop from data to deployment.

• Partner with the Data Collection team to drive collecting new data: specify what good data looks like, identify failure modes, ensure diversity and coverage.

• Work closely with external partners to ensure steady supply of high-quality pretraining-scale data.

• Run pre-/mid-/post-training on VLA stack; explore new modalities and architecture changes.

• Build and maintain continuous pipelines: ingest synthetic data and teleop logs, version them, apply weak‑supervision labelling, curate balanced datasets, and auto‑surface fresh failure cases into retraining.

• Work with MLOps & Data Platform teams to scale distributed training and optimize models for real‑time edge inference.

What We're Looking For

• 3+ years building deep‑learning systems (industry or research) with shipped models or published artifacts to show for it.

• Deep hands‑on experience with at least one of: LLMs, VLMs, or image/video generative models — architecture, training, and inference.

• Experience with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training strategies.

• Strong Python + PyTorch/JAX; you can profile, debug numerics, and write maintainable research code.

• Familiarity with modern software engineering practices.

• You document experiments clearly and communicate trade‑offs crisply.

Nice to have

• Robotics or autonomous driving experience.

• Experience applying RL to LLMs or robotics.

• Experience with VLA (vision-language-action) models.

• Proven productization of deep nets (latency/throughput constraints, telemetry, on‑device optimization).

• Publications at top-tier deep learning conferences or equivalent open‑source contributions.

• Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open source VLA frameworks.

What We Offer

• Competitive equity: stock options with meaningful upside as we scale.

• 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).

• Private healthcare, including virtual and in-person care.

• Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in-office.

• Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.

• Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role

We're hiring a Senior Autonomy Engineer focused on SLAM & Navigation to join our team. In this role, you will bridge the gap between classical spatial geometry and next-generation AI. You will lead the design and development of robust state estimation, long-term mapping, and localisation loops, with a specific focus on integrating modern machine learning techniques and foundation geometry models into our core navigation stack. Your work will ensure our robots possess rock-solid spatial awareness and execute highly reliable trajectories over extended deployments in complex, real-world environments.

What You'll Do

• Design and scale robust SLAM pipelines that maintain highly accurate localisation and state estimation across dynamic physical spaces.

• Integrate foundation geometry models and modern ML techniques into the localisation loop to enhance traditional spatial tracking, data association, and visual odometry.

• Architect and maintain robust long-term mapping systems that enable robots to autonomously update, manage, and scale spatial maps across changing environments over time.

• Build and scale auto-labeling data pipelines that leverage foundation geometry models to generate high-fidelity spatial ground truth for downstream ML training.

• Bridge classical geometry with deep learning architectures, building hybrid systems that map raw sensor data into globally consistent metric trajectories.

• Deploy and benchmark spatial AI software directly on physical robot hardware, ensuring deterministic, ultra-low latency execution on edge compute.

• Translate cutting-edge spatial AI research into production reality, continuously evaluating breakthroughs in geometric learning to guide our navigation roadmap.

What We're Looking For

• Deep expertise in classical SLAM and multi-view geometry, including extensive hands-on experience with state estimation, visual/LiDAR odometry, and multi-sensor fusion.

• Experience handling backend map optimization and solving the unique structural challenges associated with long-term mapping in large or changing physical environments.

• Practical experience applying modern ML to geometric problems, with exposure to utilizing or adapting newer foundation geometry models.

• Proven ability to build scalable data pipelines or auto-labeling workflows tailored for geometric and spatial datasets.

• Proficiency in C++ and Python, with a track record of writing clean, highly parallelized, production-grade algorithmic code.

• Hands-on experience deploying navigation systems on physical hardware, with a deep understanding of the practical edge constraints of real-world robotics.

• A research-to-production mindset, capable of tearing through the latest CVPR/ICRA papers and figuring out exactly how to make those models run with bulletproof reliability.

What We Offer

• Competitive equity: stock options with meaningful upside as we scale.

• 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).

• Private healthcare, including virtual and in-person care.

• Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in-office.

• Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.

• Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role

We are looking for a Controls Engineer to join our Control Team in Boston.

You will own how we know our controls stack works: the testing and validation infrastructure that turns "it looked fine on the robot" into measured, reproducible evaluation, the observability and failure analysis that makes runtime behaviour visible and failures shareable, and the documentation and runbooks that let the team self-serve without institutional knowledge. You will also strongly contribute to first-time bring-up of new hardware for Boston components and validate changes end-to-end on real robots before the wider team depends on them.

The ideal candidate has strong control fundamentals, solid software engineering discipline across the stack - from control code to test harnesses to diagnostic tooling - and the debugging instincts that only come from real hardware. You will work across the whole control stack and be the person the team relies on to tell them the truth about their code.

What You'll Do

Testing & Validation Infrastructure:

• Build and own hardware-in-the-loop (HIL) and integration test workflows that quantify controller and motion repeatability and accuracy - turning "it looked fine on the robot" into measured, reproducible evaluation.

• Define and implement repeatability and accuracy metrics for controller and motion changes, and the harnesses that make those measurements consistent across runs and across robots.

• Expand unit and integration test coverage across the controls components the team actually runs - actuator drivers, hardware interfaces, whole-body control, and the teleoperation pipeline.

• Develop automated regression checks that surface controls regressions - in accuracy, repeatability, or behaviour - in simulation and on hardware before they reach the wider team.

• Work with controls engineers to define testability requirements for new components and algorithms, so things are built to be evaluated and validated.

• Package controllers into cleanly separable, reusable, and easily testable interfaces - so individual controllers can be developed, swapped, and validated in isolation.

New Hardware Bring-Up & Integration:

• Strongly contribute to first-time bring-up of new hardware for Boston components, and to their integration into the controls stack.

• Validate hardware and software changes end-to-end on real robots before broader team use - structured, documented, and repeatable.

Debugging, Observability & Failure Analysis:

• Instrument the controls stack to improve visibility into runtime behaviour - logging, tracing, and diagnostic tooling.

• Reproduce hardware and software failures in structured, developer-shareable formats; feed structured root-cause context back to algorithm and hardware owners.

• Identify and resolve cross-stack failure modes that span controls, firmware, and hardware.

Documentation & Knowledge Transfer:

• Write and maintain engineering documentation for the controls stack: HIL and test coverage, and bring-up/integration guides for new hardware.

• Own runbooks that let controls engineers self-serve validation, integration, and recovery without relying on institutional knowledge.

What We're Looking For

• Substantial hands-on robotics experience on real hardware.

• Strong control theory foundation (joint-space control, PID and feedforward, impedance/admittance, observers, state estimation, filtering, stability) — enough to define meaningful repeatability and accuracy metrics for a control stack and interpret what they say.

• Shipped software across the stack: modern C++ inside a real-time control codebase, plus Python for test harnesses, analysis and tooling.

• Built test automation, HIL or integration-test infrastructure for complex physical systems — and got other engineers to actually use it.

• Solid measurement and data analysis judgement: sampling, timing and synchronisation, noise, statistical significance, and knowing when a difference between two runs is real.

• Strong debugging across software/firmware/hardware boundaries, with the discipline to reproduce failures in a form other engineers can act on.

Nice to have:

• Physics simulation environments (MuJoCo, Isaac Sim/Isaac Lab) and sim-to-real validation.

• Observability tooling: logging and tracing frameworks, metrics collection, time-series databases, dashboarding (e.g. Grafana).

• First-time hardware bring-up experience: new actuators, sensors or compute targets integrated into a control stack.

• A track record of engineering documentation and runbooks that outlived their author.

• Release management or quality gates for safety-relevant software.

What We Offer

• Comprehensive health coverage for US‑based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources.

• Meaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays.

• 401(k) retirement plan with 4% employer match.

• Competitive equity: stock options with meaningful upside as we scale.

• Free daily catered lunch, snacks, and drinks in‑office.

• Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.

• Freedom to influence the product and own key initiatives.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About The Role

We're hiring a strong Robotics Learning Engineer to join our Manipulation team based in London.

In this role, you will work on teaching our robots to manipulate the world around them.

This is a role at the intersection of applied deep learning and robotics, and to be set up for success you need both experience of working with real robot hardware (e.g. identifying issues in control or teleop), and applied deep learning (you don’t have to be an expert on cutting edge neural network techniques, but you should be perfectly capable of curating data, fine-tuning a policy on that data and hypothesising potential mitigations when something doesn’t work).

What You’ll Do

• Post-train manipulation policies via behaviour cloning and RL; own the full loop from data to deployment.

• Come up with data preprocessing strategies to improve the quality of collected data.

• Work with the simulation team to set up RL training using digital twin, and then iterate on reward and simulation quality to ensure successful transfer to the real world.

• Partner with the data collection organization to drive data collection activities for a specific capability: specify what good data looks like, ensure diversity and coverage, and iterate on instructions.

• Expand observation and action spaces with new components required to support novel capabilities, and work with the Teleoperations team to expose these components to robot operators.

• Partner with Teleoperations and Controls teams to improve motion smoothness and teleoperation experience.

• Interface with hardware design team to ensure that manipulation team findings regarding the current generation of hardware are reflected in future designs.

What We're Looking For

• 3+ years working on robots (industry or research) with shipped artifacts to show for it. A good understanding of modern teleoperation and low-level control stack.

• Experience with neural network post-training.

• Familiarity with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training, PyTorch or JAX. Ability to profile & debug numerics and write maintainable research code.

• Good familiarity with modern software engineering practices.

• Ability to document experiments clearly and communicate trade‑offs crisply.

Nice to have:

• Experience training VLA models for manipulation (autoregressive, diffusion or flow-matching based). Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open VLA frameworks.

• Experience applying RL to robotics problems.

• Publications at top-tier robotics or deep learning conferences or equivalent open‑source contributions.

What We Offer

• Competitive equity: stock options with meaningful upside as we scale.

• 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).

• Private healthcare, including virtual and in-person care.

• Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in-office.

• Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.

• Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role

We're looking for a Firmware Engineer to develop and maintain the embedded software behind the end effectors on our robots and the human-worn devices operators use to interface with them. This role combines firmware development with hardware integration you'll sit at the boundary between hardware and software, bringing up new PCB revisions, writing firmware and drivers, and integrating a wide range of sensors and compute platforms. You'll work closely with electrical and mechanical engineers in a high-paced environment where priorities shift fast and reliability matters.

What You'll Do

• Develop Embedded Firmware: Write and maintain firmware for embedded microcontrollers, covering sensor sampling, status indication, input handling and power management.

• Integrate Sensors & Drivers: Integrate and write drivers for sensors, encoders, LCD screens, IMUs, ToF sensors, LiDARs and cameras, including MIPI and other interfaces.

• Work Across Compute Platforms: Integrate device-level firmware with higher-level compute platforms such as ESP32, Raspberry Pi and NVIDIA Jetson, and similar Linux-based platforms.

• Implement Communication Interfaces: Design and implement interfaces between hardware subsystems, including I2C, SPI, UART, Ethernet, USB, CAN, EtherCAT and MIPI.

• Bring Up New Hardware: Review schematics, debug boards with an oscilloscope/logic analyzer, and resolve integration issues spanning firmware, electrical and mechanical.

• Own Calibration & Fault Detection: Develop calibration routines, power-sequencing logic, and fault/status detection for sensors and mechatronic systems.

• Support Component Selection: Help with component selection for sensors, MCUs and other hardware building blocks.

• Maintain OTA Pipelines: Build and maintain OTA update and image provisioning pipelines for fleets of embedded devices.

What We're Looking For

• Degree in Electrical/Computer Engineering, Computer Science, or a related field, with 4+ years' experience in embedded firmware development (C/C++).

• Hands-on experience with microcontroller and compute platforms such as ESP32, STM32, Raspberry Pi and NVIDIA Jetson.

• Experience integrating and/or writing drivers for sensors and peripherals — encoders, IMUs, ToF sensors, LiDARs, cameras and LCD/display modules.

• Solid understanding of embedded communication and sensor interfaces: I2C, SPI, MIPI, UART, Ethernet/TCP-IP, USB, CAN and EtherCAT.

• Comfortable bringing up and debugging new hardware revisions, with strong skills using an oscilloscope, logic analyzer and JTAG/SWD.

• Experience developing calibration routines and supporting component selection alongside electrical and mechanical engineers.
  
  Nice to have

  • FPGA experience

  • Experience with camera synchronisation or multi-sensor time-sync

  • Python skills for tooling, test scripts, or diagnostics

  • Experience working with formally defined hardware interfaces/contracts shared across teams

What We Offer

• Competitive equity: stock options with meaningful upside as we scale.

• 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).

• Private healthcare, including virtual and in-person care.

• Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in-office.

• Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.

• Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role:

We are looking for a Software Engineer to own the device software and data pipeline for our UMI data collection devices - handheld gripper systems used by human operators to demonstrate manipulation tasks. The data they produce is used to train our robots, so the quality of what you ship determines the quality of robots we deploy.

This is a deeply technical, hands-on role. You will write production-grade device software, build reliable sensor fusion and recording pipelines, and own the validation tooling that keeps our training datasets clean. You will work closely with hardware, AI, and data collection teams.

What You’ll Do:

• Develop and maintain device software across the full episode lifecycle: session initialisation, per-sensor stream management, episode recording, and graceful shutdown

• Integrate and synchronise sensor streams - wrist and head cameras, 6-DOF pose trackers, gripper aperture encoders, and optionally force/torque sensors - into temporally-aligned, policy-consumable trajectories

• Define and maintain the data contract between UMI devices and the AI team: stream formats, episode packaging, metadata schemas, and the interface between raw recordings and training pipelines

• Build and maintain data validation tooling that detects dropped frames, timing jitter, pose tracking loss, image quality degradation, and sensor faults before corrupt episodes enter the training dataset

• Own operator-facing device software: status indication, start/stop/cancel episode controls, and clear feedback when a session needs to be retried

• Support field data collection sessions - deploying devices to operators, validating data quality in situ, and iterating quickly when issues surface during collection

• Debug integration failures on device hardware: camera driver issues, bus bandwidth saturation, tracker calibration drift, compute thermal throttling, and storage write failures mid-episode

We’re Looking For:

• Experience in embedded or device-level software in a robotics or sensing context - writing code that runs on the device, not just talking to it

• Proficiency in C++ and/or Python for real-time sensor drivers, inter-process communication, and data recording pipelines

• Solid understanding of multi-modal sensor synchronisation - timestamps, hardware triggers, clock drift - and the practical consequences of getting it wrong for downstream ML

• Familiarity with camera pipelines and the difference between what a sensor reports and what actually lands on disk with correct timing

• Strong instincts around data quality and dataset hygiene - you are uncomfortable shipping episodes with frame drops, tracking loss, or misaligned streams

• Proven ability to debug on real hardware: you read logs, attach profilers, and can diagnose whether a problem is a driver, a bus, or a timing issue

Nice to have:

• Experience with 6-DOF pose tracking systems (VIO, optical trackers, or similar) and their common failure modes

• Familiarity with ML training data formats and what an AI team actually needs from a recorded episode - understanding the consumer of the data you produce

• Exposure to operator-facing tooling for data collection: session management, per-episode quality summaries, rejection and retry workflows

• Experience scaling device software from a small number of prototype units to many devices operated by non-engineers in the field

What We Offer

• Competitive equity: stock options with meaningful upside as we scale.

• 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).

• Private healthcare, including virtual and in-person care.

• Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in-office.

• Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.

• Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role

We are looking for a Robotics Test Engineer to support software release validation, policy evaluations, and end-to-end metrics collection on our humanoid robots. You will work alongside our Test Team, owning day-to-day execution and growing into deeper HIL and automation responsibilities.

This is not a standard web-QA role. You will be running tests on real robots, comparing simulation against reality, and helping us build the data pipeline that tells us whether each new software version is ready to ship.

What You'll Do

Software Release Testing

• Release Validation: Execute the end-to-end test pipeline for each new software release, ensuring quality gates are met before the build is deployed to the fleet.

• Regression Coverage: Run automated and manual regression suites against new builds; triage failures and route them to the right owner.

• CI/CD Participation: Contribute new tests to our CI/CD pipeline (GitLab CI, GitHub Actions) so that regressions are caught immediately after code merges.

2. Policy Evaluations

• Eval Support: Help design and run policy evaluations for our learned behaviors — defining success criteria, executing trials, and collecting results in a reproducible way.

• Simulation: Run policy evaluations in simulation environments (Gazebo, NVIDIA Isaac Sim) in parallel with physical robot tests.

• Sim-to-Real: Track differences between simulation and physical robot results and feed findings back to the policy team.

3. E2E Metrics Collection

• Metrics Pipeline: Support the collection of end-to-end performance and reliability metrics across releases, building consistent reporting the org can trust.

• Dashboards: Help maintain dashboards that highlight pass/fail rates, latency, and performance trends release-over-release.

• Data Hygiene: Keep test data clean and well-labeled so that long-term trends remain meaningful as the platform evolves.

What We're Looking For

• Experience: 3+ years in software test engineering or test automation, ideally with some exposure to robotics, embedded systems, or another physical-systems domain.

• Coding: Strong proficiency in Python for scripting and test automation. Comfortable reading C++.

• Robotics Middleware: Working knowledge of ROS2 — you understand topics, services, and how to interact with a running robot.

• OS: Comfortable in Linux (Ubuntu) — terminal, shell scripting, basic system administration.

• Mindset: Methodical and curious. You enjoy finding the one weird edge case that breaks the build.

Nice-to-Have:

• Experience with robotics simulators (Gazebo, NVIDIA Isaac Sim, Unity).

• Exposure to Hardware-in-the-Loop (HIL) test benches.

• Basic electrical debugging skills (multimeter, oscilloscope).

• Awareness of safety-critical standards (IEC 61508, ISO 26262).

Tech Stack

• Languages: Python (primary), C++ (reading), Bash

• Robotics: ROS / ROS2

• CI/CD: GitLab / GitHub Actions

• Simulation: NVIDIA Isaac Sim

• Hardware Interfaces: CAN, EtherCAT, Ethernet

What We Offer

• Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays.

• Fully funded private healthcare for UK employees, with broad provider access, virtual and in‑person care, and strong mental health and serious illness support.

• Equity included–we believe builders should share in what they build.

• Pension scheme with a total 8% contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in‑office.

• Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.

• Freedom to influence the product and own key initiatives.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role

We are looking for a Software Test Engineer to own the quality of the software products that live around our robots — the humanoid console, the inference servers infrastructure, and the backend services that connect everything together.

This is a software-first role. You will not need to bolt on a HIL bench or wire up sensors. You will be testing APIs, web UIs, distributed services, and the infrastructure that runs our models. You will work closely with backend engineers, frontend developers, and the ML platform team.

What You'll Do

• Console Testing: Own the quality of the humanoid operator console — front-end behavior, API contracts, edge cases, and the user-facing flows operators rely on.

• Inference Infrastructure: Test the inference servers and model-serving stack — latency, throughput, failover, version rollouts.

• Backend Services: Validate backend services and their APIs — auth, data pipelines, telemetry, fleet management — including contract testing and integration testing.

• Test Automation: Design and implement automated test suites that run in CI/CD; expand coverage as the platform grows.

• Quality Strategy: Define test methods, quality criteria, and metrics; participate in shaping the overall testing strategy for the software platform.

• Documentation: Document tests in our test tracking system and keep internal documentation accurate.

What We're Looking For

• Experience: 4+ years in software testing, with strong experience testing client-server systems (front-end, back-end, APIs).

• Test Design: Strong grasp of testing theory and test design techniques — equivalence partitioning, boundary analysis, state-based testing, and similar.

• Automation: Hands-on Python for test automation. Familiarity with an API testing framework (pytest + requests, or equivalent).

• Linux: Comfortable operating in Linux environments and interacting with services over the terminal.

• Version Control: Experience with Git.

• CI/CD: Understanding of CI/CD pipelines and how automated tests integrate into them.

• Test Tracking: Experience with a test management or task tracking system (Jira, TestRail, or similar).

Nice-to-Have:

• Front-end test automation (Selenium, Playwright, Cypress).

• Performance and load testing (k6, Locust, JMeter).

• Containerization (Docker, basic Kubernetes).

• Familiarity with ML model serving infrastructure (Triton, TorchServe, etc.) and the kinds of things that can go wrong there.

• Knowledge of one other language (JavaScript/TypeScript, Go, or C++).

• Awareness of the robotics domain — knowing what a humanoid robot needs from its software stack.

Tech Stack

• Languages: Python (primary), JavaScript/TypeScript for front-end work

• Backend: REST/gRPC APIs, message queues

• Infrastructure: Linux, Docker, cloud (AWS/GCP)

• Tooling: Git, GitHub/GitLab, test management tooling

What We Offer

• Competitive equity: stock options with meaningful upside as we scale.

• 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).

• Private healthcare, including virtual and in-person care.

• Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in-office.

• Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.

• Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

We are building a world-class robotics organisation across London, Vancouver and Boston to solve some of the hardest problems in humanoid robotics, including integrating complex hardware, embedded systems, AI, and large-scale robotic platforms into cohesive, production-ready systems.

If you are excited about driving large-scale, cross-functional robotics programs from concept to real-world deployment, then we're keen to hear from you.

About the role (Intro):

As a Technical Program Manager at Humanoid, you will own the planning and execution of complex robotics development projects, ensuring predictable delivery of our highly integrated humanoid systems and our roadmap of capabilities for deployment at customer sites. You will lead cross-functional development with an emphasis on software/AI on new hardware, coordinating closely with our teams in Boston, Vancouver, and San Diego.

This is a high-impact role requiring strong technical judgment, systems thinking, and the ability to drive execution across deeply interdependent teams.

Establish processes that work

The nature, method, and velocity of software development is changing fast. Yet the iron triangle of project management (scope, schedule, budget) remains. The TPM must apply, build, and evolve processes and tools to manage this.

What Makes This Role Exciting

• Drive execution of next-generation humanoid robot programs from concept to deployment

• Work at the intersection of hardware, embedded systems, AI, robotics, and production

• Coordinate globally distributed engineering teams spanning multiple time zones

• Tackle the complex challenges of scaling robotics systems into products that work in the real world

What you'll own:

Own the end-to-end planning and execution of a portfolio of projects in a robot new product introduction program, where you'll be accountable for scope, schedule, cost, and process. Your portfolio includes software and hardware projects, all of which are deeply cross-functional, spanning Systems, Safety, Mechanical, Electrical, Firmware, Software, AI/ML, DFX, Regulatory, Integration, Test, Supply Chain, Design, Product, Marketing, Logistics, and more.

Drive execution

Track and motivate project progress end-to-end, coordinating across many teams, sites, and suppliers to predictably execute the plan. Proactively anticipate risks, put mitigation plans in place, and manage them actively. Urgently identify, prioritise, and clear blockers.

Lead people and stakeholders

Empathise with, partner with, negotiate with, and manage stakeholders, using tactful and effective approaches to build alignment and secure commitments. Establish efficient, clear, and timely program communication, tailored to your audience and optimised for the real challenges of collaborating across distances, cultures, and time zones.

Bring judgment

Based on situational awareness, operate fluidly between the strategic and the detailed. Apply systems thinking, perspective, and technical judgment to bring clarity, prioritisation, and guidance to your teams.

Embody the culture

Roll up your sleeves and enthusiastically pitch in wherever it's needed for the program's success at Humanoid because we're all in this together. Never settle for the status quo and play a key role in proactively improving our practices. Demonstrate through your actions how you contribute to the team's success, building strong, enduring influence across the program team and its stakeholders.

What we're looking for from you:

• 3+ years of relevant post-graduate experience as a project or program manager for development of leading-edge software product development

• Bachelor's or Master's degree in a technical field relevant to software, AI, or robotics

• Technical background in development of complex systems that integrate new hardware, firmware, and software

• Experienced in modern tech software development processes and tools

• Exposure to hardware development and new product introduction

• Proficiency with multiple program management methodologies and tools

• Proven ability to create structure and clarity in ambiguous, fast-paced environments, managing influential stakeholders

• Strong organisational skills with the ability to manage multiple complex workstreams simultaneously

• Impressive written and verbal communication skills, both synchronous and asynchronous

• Demonstrated ability to lead through influence across diverse teams

• Ability to remain calm, structured, and effective under pressure, including with executive stakeholders

• Strong ability to understand and communicate complex technical concepts

• Systems-thinking mindset with strong problem-solving capabilities

• Adept applying AI to project management and development workflows

• Flexibility to shift hours as needed to collaborate with our international team

Bonus Qualifications

• Experience in robotics, autonomous systems, or advanced hardware companies

• Experience in production development

• Experience working in speed-focused startup environments

• Experience across end-to-end lifecycle, from R&D to production

• Experience working with globally distributed teams

Why Join Humanoid

• Competitive salary plus participation in our Stock Option Plan

• Collaboration with top-tier engineers, researchers, and product experts in AI and robotics

• Freedom to influence the product and own key initiatives

• Ability to solve some of the most complex engineering challenges in robotics for the real world

• Meaningful time off to rest and recharge: 23 days of annual leave, plus bank holidays and concessionary days over the Christmas period.

• Comprehensive extended health benefits starting on your first day, including fully paid medical and dental, virtual care, employee and family assistance, and worldwide emergency medical support

• Free daily catered lunch, snacks, and drinks in-office

How to Apply

Does this role sound like the perfect fit for you? If it does, then please apply here, complete the application process and we'll be in touch soon!

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About The Role

We're hiring a Senior Dev/MLOps Engineer to join our Data & Compute Platform team based in London.

What You’ll Do

• Own and manage the full lifecycle of both ML models and core infrastructure - from development and deployment to monitoring and continuous improvement.

• Build and maintain robust CI/CD pipelines for both software and ML workflows.

• Ensure reliability, scalability, observability, and security of production systems and ML infrastructure.

• Automate deployment, orchestration, and environment management using modern DevOps tooling.

• Collaborate closely with software engineers, data scientists, and product teams to bring ML-powered features to production.

• Proactively detect, troubleshoot, and resolve infrastructure and model performance issues.

• Stay up to date with industry best practices in DevOps, MLOps, and infrastructure engineering.

• Document infrastructure, workflows, and operational procedures clearly and thoroughly.

What We're Looking For

• Proven experience in a senior-level DevOps, MLOps, or related infrastructure-focused engineering role.

• Strong proficiency in Python and familiarity with ML frameworks such as TensorFlow or PyTorch.

• Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools (Docker, Kubernetes).

• Solid understanding of CI/CD systems (e.g., GitHub Actions, GitLab CI, ArgoCD) and infrastructure-as-code tools (e.g., Terraform, Helm).

• Familiarity with data engineering concepts such as ETL pipelines, data lakes, and large-scale batch/stream processing.

• Ability to design scalable, secure, and observable systems in fast-moving environments.

• Strong debugging and problem-solving skills across distributed systems.

• Excellent collaboration and communication skills, with experience working in cross-functional teams.

• Understanding of security and compliance best practices for both software and ML systems.

What We Offer

• Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays.

• Fully funded private healthcare for UK employees, with broad provider access, virtual and in‑person care, and strong mental health and serious illness support.

• Equity included–we believe builders should share in what they build.

• Pension scheme with a total 8% contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in‑office.

• Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.

• Freedom to influence the product and own key initiatives.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role

As a VP of AI Transformation will be responsible for defining and executing Humanoid's enterprise-wide AI transformation strategy.

This leader will establish the vision, operating model, governance framework, and execution roadmap required to enable AI adoption across all business functions. Working closely with the CEO, Executive Leadership Team, Business Transformation, IT, Engineering, and functional leaders, you will drive Humanoid's evolution into an AI-native company.

You will lead the AI Transformation Office and oversee a cross-functional team, including AI Leads across Engineering, Business Operations, Back Office Functions, and Executive Operations. You will ensure that every AI initiative delivers measurable business value while maintaining the highest standards of security, compliance, governance, and operational excellence.

This is a highly strategic leadership role with significant influence over the future operating model of the company.

What You'll Do:

AI Transformation Strategy

• Define and execute Humanoid's enterprise AI transformation vision and roadmap.

• Develop a company-wide AI strategy aligned with business objectives and growth plans.

• Establish priorities, investment frameworks, and governance structures for AI initiatives.

• Advise executive leadership on emerging AI opportunities, risks, and market developments.

• Build an AI-first culture focused on innovation, productivity, and continuous improvement.

• Drive the adoption of AI agents, intelligent automation, and AI-enabled workflows across the organization.

AI Operating Model & Continuous Improvement

• Own and evolve Humanoid's AI-Powered Continuous Improvement Flywheel.

• Establish transformation governance, operating cadences, reporting mechanisms, and executive review forums.

• Embed AI initiatives into business planning, capability maturity assessments, and operational reviews.

• Identify, prioritize, and scale high-impact AI use cases across all functions.

• Ensure successful pilots are translated into enterprise-wide capabilities.

• Drive the development of AI-native ways of working across the organization.

Enterprise AI Governance

• Establish policies, standards, and controls for responsible AI deployment.

• Define governance frameworks covering:

• AI ethics and responsible AI

• Security and cyber risk management

• Data governance and privacy

• Human-in-the-loop controls

• Model evaluation and monitoring

• Compliance and audit readiness

• AI vendor and platform governance

• Ensure all AI solutions align with corporate, legal, and regulatory requirements.

Organizational Transformation & Change Management

• Lead enterprise-wide AI adoption and change management programs.

• Build AI literacy across leadership teams and employee populations.

• Establish AI Champions networks and communities of practice.

• Drive workforce enablement and behavioral change initiatives.

• Foster a culture where AI augments human capabilities, accelerates decision-making, and improves productivity.

Business Impact & Value Realization

• Define KPIs and success metrics for AI transformation initiatives.

• Measure and report:

• Automation maturity

• Productivity improvements

• ROI of AI initiatives

• User adoption

• Quality and accuracy outcomes

• Cost efficiencies

• Operational performance improvements

• Present transformation progress, outcomes, and strategic recommendations to the Executive Leadership Team and Board.

Cross-Functional Leadership

• Lead and mentor AI Leads and transformation teams across the business.

• Partner closely with:

• CEO and Executive Leadership Team

• Business Transformation

• Engineering

• IT

• Finance

• HR

• Supply Chain

• Compliance

• Cybersecurity

• Align AI initiatives across functions to avoid duplication and maximize business impact.

• Promote collaboration between technical and business teams.

Innovation & External Ecosystem

• Continuously evaluate emerging AI technologies, platforms, and market developments.

• Build relationships with AI vendors, research institutions, industry partners, and startups.

• Identify opportunities to create competitive advantage through AI.

• Benchmark Humanoid against leading AI-native organizations and establish best practices.

What We're Looking For

• 10+ years of experience in business transformation, digital transformation, enterprise technology, AI strategy, or AI leadership roles.

• Proven track record leading large-scale organizational transformation programs.

• Deep understanding of artificial intelligence, machine learning, generative AI, agentic AI systems, automation, and enterprise AI platforms.

• Experience designing enterprise operating models, governance frameworks, and transformation programs.

• Strong understanding of business process transformation and continuous improvement methodologies.

• Experience leading cross-functional initiatives involving business, technology, and operations teams.

• Exceptional executive communication and stakeholder management skills.

• Strong analytical, strategic, and systems-thinking capabilities.

• Demonstrated ability to translate emerging technologies into measurable business outcomes.

• Experience building AI adoption programs at enterprise scale.

Nice to have:

• Experience building AI Centers of Excellence (CoE) or enterprise AI programs.

• Experience deploying AI agents and intelligent automation solutions at scale.

• Background in robotics, advanced manufacturing, industrial automation, or deep-tech organizations.

• Familiarity with Lean, Six Sigma, capability maturity frameworks, and operational excellence methodologies.

• Experience with enterprise knowledge management and AI-driven decision support systems.

• MBA or advanced degree in Engineering, Computer Science, Business, or a related field.

What Success Looks Like:

Within your first 12 months, you will have:

• Established Humanoid's AI Transformation Office and governance framework.

• Embedded AI maturity assessments into business capability reviews.

• Delivered multiple AI initiatives with measurable business impact.

• Built and operationalized an AI-first operating model across engineering and business functions.

• Increased automation maturity across critical value streams.

• Improved productivity through AI-enabled workflows and intelligent automation.

• Created a sustainable AI adoption culture supported by governance, training, and continuous improvement.

• Positioned Humanoid as one of the world's leading AI-native robotics companies.

What We Offer

• Meaningful time off to rest and recharge: 23 days of annual leave (accrued), separate sick leave, and paid bank holidays and company holidays.

• Fully funded private healthcare for UK employees, with broad provider access, virtual and in‑person care, and strong mental health and serious illness support.

• Pension scheme with a total 8% contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in‑office.

• Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.

• Freedom to influence the product and own key initiatives.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the role:

We are looking for a Software Engineer to work on the systems that let operators author, deploy, and manage robot workflows at scale. This sits at the intersection of backend infrastructure and product - you'll build the services that coordinate fleets of robots, the tooling that lets operators express what they want robots to do, and the interfaces that give visibility into what's actually happening on the floor.

This is a full-stack role with a strong backend lean. You'll work closely with the robotics, AI, and product teams to build systems that are real-time, multi-tenant, and mission-critical.

What You’ll Do

• Build and maintain backend services that coordinate robot fleets at runtime: workflow state management, event logging, and the APIs that robots, operators, and third-party systems use to interact with the platform

• Develop and evolve the workflow authoring experience - tooling that lets operators define, deploy, and incrementally refine robot workflows in natural language, without needing to understand the underlying representation

• Build on-robot services that enable remote control, workflow execution, state reporting, and diagnostics

• Own the data infrastructure that tracks workflow execution: event logs, conformance metrics, and the audit trails that let operators understand what robots are doing and why

• Build and maintain reliable, secure cloud infrastructure for running these services, including deployment pipelines, observability, and alerting

• Implement testing and validation pipelines to catch regressions across the UI, backend, and on-robot services - including simulation-based workflow validation before changes hit production

What We’re Looking For

• Strong backend engineering skills in Python, Go, or similar

• Solid understanding of API design, data modelling, and the tradeoffs in distributed systems (consistency, concurrency, fault tolerance)

• Experience with cloud infrastructure and deployment: containerisation, CI/CD, infrastructure-as-code

• Comfort working across the stack from frontend to backend

• Experience with observability and alerting in systems where failures have real operational consequences

• Good instincts for where complexity should live and how to keep systems debuggable and understandable as they grow

Nice To Have

• Familiarity with workflow engines, state machines, or coordination systems — ideally in a multi-agent or fleet context

• Experience building operator-facing tooling: dashboards, authoring UIs, or systems that translate human intent into structured actions

• Exposure to LLM-based agentic systems, particularly using AI to generate or modify structured representations from natural language

• Experience integrating with third-party enterprise systems (WMS, ERP, or similar)

• Background in robotics or real-time systems where execution state and side-effects need to be managed carefully

What We Offer

• Competitive equity: stock options with meaningful upside as we scale.

• 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).

• Private healthcare, including virtual and in-person care.

• Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in-office.

• Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.

• Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role

We’re looking for a Software Engineer II to join our Platform Infrastructure team in San Diego. You’ll help build the software and tools that enable our robots to run trusted software on trusted hardware, working with security, firmware, and platform engineers across the device lifecycle.

What You'll Do

• Build and maintain software and tools for trusted boot and device provisioning, working with NVIDIA secure boot and UEFI. For example, you might help bring up a secure boot flow on a new device or build tooling to provision and verify device credentials.

• Contribute to device trust and key protection using hardware roots of trust, including Trusted Platform Modules (TPMs), and security technologies such as ARM TrustZone.

• Contribute to device key management though the use of Hardware Security Modules (HSMs).

• Write, test, and debug software and scripts in Linux, and investigate issues across software and hardware.

• Identify and reduce attack surfaces across device software, boot flows, and supporting tools.

• Collaborate with security, firmware, cloud, manufacturing, and other engineering teams through design discussions, code reviews, and documentation; own well-scoped projects from design through implementation and testing, with input from experienced teammates.

What You Bring

You’re a curious, collaborative engineer who takes ownership, works through unfamiliar problems, and wants to deepen your skills in device security. You’ll bring:

• Software engineering experience — Typically 1–3 years of full-time experience building, testing, and maintaining production-quality software, or equivalent experience.

  • You have a strong foundation in object-oriented programming and software design.

  • You can read and reason about code, identify logic errors, and learn to contribute across C++, Python, and Rust codebases

  • Prior experience in all three languages is not required. B.S. or M.S. in CS, CE, EE, or a related field.

• AI-assisted development — You’re comfortable using AI-assisted development tools and can understand, review, and validate the code they produce.

• Security fundamentals — Familiarity with authentication, encryption, cryptographic keys, and trust boundaries, and an interest in applying them to hardware devices.

• Linux and tooling — Comfort working in Linux and using scripting languages such as Python or Bash to automate tasks, build tools, and investigate problems.

• Problem-solving and collaboration — A thoughtful approach to unfamiliar problems, attention to detail, and the ability to communicate clearly, seek feedback, and follow work through.

• Experience with key management and/or NVIDIA platforms, such as Jetson, is a plus

• Ability to work on-site at our San Diego office.

What We Offer

• Comprehensive health coverage for US‑based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources.

• Meaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays.

• 401(k) retirement plan with employer match.

• Equity included–we believe builders should share in what they build.

• Free daily catered lunch, snacks, and drinks in‑office.

• Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.

• Freedom to influence the product and own key initiatives.

For this role in California, the expected base salary range is $123,000-$154,000 USD per year; your placement in that range depends on how your experience maps to our internal leveling.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role

The Robotics Applied Research Lead establishes and leads Humanoid’s AI research and engineering function.

You decide which Physical AI data problems we work on, define how we test them, and stay directly involved in the most important technical work. You connect four areas that often sit apart:

1. Multimodal and embodied data

2. Transformer-based models and how data impacts robot policies

3. Rigorous offline and real-world evaluation of policies

4. Deployment of models in the data ecosystem

This is a player-coach role. In the first year, at least half of your time is direct technical work: designing models and experiments, reviewing or writing code, inspecting data, debugging training, examining failures, and reviewing robot rollouts.

You will also build a small research and engineering team. Add people only when the work requires them.

Mandate

Turn Humanoid data and technical access into measurable advances in Physical AI systems.

You own the answers, and the evidence, to questions such as:

• Which model families should we train, adapt, or evaluate?

• Which data produces meaningful gains in robot performance?

• What coverage, sensors, annotations, and quality controls do the models require?

• Which offline measurements predict real-world robot performance?

• Where should we adapt existing open models rather than train from scratch?

• What should Humanoid build itself, and what should it reuse or obtain through partners?

What You'll Do

• Set the technical direction: Define a focused research and engineering roadmap. Select a small number of high-value bets with clear hypotheses, baselines, milestones, and stop criteria. Decide what we build, adapt, license, or access through partners. Drop work that no longer has a strong case. Likely scope includes vision-language-action models, multimodal Transformers, robot foundation models, action representation, imitation and reinforcement learning, world models, cross-embodiment transfer, data-efficient adaptation, and robot-policy evaluation.

• Own Transformer research and engineering: Design, adapt, train, and evaluate Transformer-based systems for embodied tasks. Make the architecture and training decisions yourself. Start from strong existing models and baselines. Train from scratch only when evidence supports the cost. Build or review the critical code.

• Connect models to data strategy: Define the data needed to train and evaluate the selected models. Specify sensors, modalities, annotations, mixtures, and quality controls. Measure the effect of data quality, diversity, and composition on model behavior. Distinguish data volume from data value. You set technical data requirements; you do not run annotation workforces or field collection.

• Own evaluation: Establish offline and real-world evaluation systems, baselines, held-out conditions, and release gates. Guard against leakage, overfitting, and weak success definitions. Compare offline metrics with real-robot outcomes. A benchmark score alone is not a successful result. The evaluation must support a decision.

• Move work onto physical systems: Take projects from problem definition through training, hardware integration, and real-world testing. Design safe test plans and staged deployment. Analyse failures across data, perception, model, control, hardware, and environment. Validate material claims on physical systems.

• Build a small technical team: Recruit a few complementary researchers and engineers. Lead architecture, experiment, code, and failure reviews. Keep the team focused on validated results, not paper count, benchmark theatre, or headcount.

• Represent the function and own responsible development: Explain the strategy to customers, partners, and investors. Convert customer needs into testable technical requirements. State uncertainty and limits clearly. Define safety constraints, supervision, and rollback paths for physical trials. Require reproducible evidence before making capability or safety claims.

What We're Looking For

• Deep, direct Transformer expertise: This is a hard requirement. You must have personally made material architecture or training decisions in one or more substantial Transformer-based systems, such as vision Transformers, VLMs, VLAs, multimodal foundation models, Decision Transformers, diffusion Transformers, video Transformers, world models, or Transformer-based perception, planning, or control. You should be able to explain, in detail, how you represented inputs and outputs, tokenized data, fused modalities, structured attention and temporal context, chose losses, built the data mixture, distributed and monitored training, diagnosed failures, and what you personally changed and why it affected task performance. Using hosted model APIs, prompting language models, or running an unchanged public training recipe does not meet this requirement.

• Physical AI or embodied-system experience: You have worked on machine learning for a system that perceives or acts in the physical world: robotics, autonomous vehicles, drones, industrial automation, manipulation, mobile robots, humanoids, wearable or egocentric systems, or similar. At least one substantial project progressed beyond an offline dataset into a real or operational physical system. Simulation-only experience is not sufficient unless you also owned credible sim-to-real transfer and physical validation.

• Hands-on technical ability: You write and review high-quality Python. You work directly with PyTorch or an equivalent framework. You can read unfamiliar model and training code, design and debug experiments, inspect failures and rollout traces, work with large multimodal datasets, and make informed decisions about compute, memory, latency, and cost.

• Technical leadership: You have set direction for important technical work: a research or engineering group, a major model or robotics programme, or a cross-functional project you owned. You have hired or mentored researchers or engineers, made architecture and resource decisions, stopped weak work, and taken a result into deployment. A management title is not required. Direct ownership is.

• Evaluation, communication, and judgment: You design held-out tests, run controlled comparisons, find leakage and confounds, and report results with appropriate uncertainty. You separate evidence from belief, state what remains unknown, and reduce broad research questions to testable work.

• Strong preference - Computer Vision: We are particularly interested in candidates who combine deep expertise in Transformer architectures with a strong background in computer vision. Relevant experience may include visual representation learning, vision-language models (VLMs), video and temporal modelling, object detection, segmentation, tracking, multi-view and egocentric vision, 3D and spatial reasoning, pose estimation, calibration, localisation, sensor fusion, or real-time vision systems.

• Education: A PhD in machine learning, computer vision, robotics, computer science or a related field is valuable but not required. An equivalent record of original model work, technical leadership, and real-system delivery is sufficient. We care more about what you personally designed, trained, tested, and deployed than about a specific degree or number of years.

Nice-to-have:

• Technical expertise: Experience with VLA or robotic foundation models, action generation, diffusion or flow-matching policies, imitation learning, reinforcement learning, world models, robotic manipulation, cross-embodiment training, sim-to-real transfer, distributed training, ROS 2, or safety-critical systems.

• Additional experience: Research publications, open-source contributions, early-stage company experience, or direct collaboration with technical customers and research partners.

What We Offer

• Competitive equity: stock options with meaningful upside as we scale.

• 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).

• Private healthcare, including virtual and in-person care.

• Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in-office.

• Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.

• Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role

As a Senior Robotics Integration Engineer in San Diego, you will build the hardware-in-the-loop (HIL) CI/CD system that makes this routine. A firmware change, a control-stack update, or a new locomotion policy runs on physical hardware within minutes of a push. Simulation catches most regressions. Your system catches the ones that only appear when metal moves. Every pull request, validated on real HMND hardware, automatically, before it merges.

We have bench rigs, partial automation, and a strong simulation pipeline. You will harden what exists and build the next generation. You will also be the first dedicated test engineer in San Diego, and you will run HIL development as a shared effort across our offices so progress continues while one site is offline.

This is the long-term vision for HIL testing at Humanoid. You will be part of the global Integration & Test team that will set the technical direction and build the foundations. AI tools are central to how we build it. We expect you to use them heavily, from writing test platforms that can be used by all engineers to triaging failures and analyzing logs. We want someone excited to rethink how test infrastructure gets built.

What You'll do

• Build PR-triggered pipelines that schedule, run, and report hardware tests: orchestration, device allocation, firmware flashing, power and reset control, data capture, and teardown.

• Define what "tested on hardware" means. Build and grow regression infrastructure across motion control, locomotion, manipulation, perception, safety, and power, and enabling each new robot capability to be developed with automated coverage as it ships.

• Design and run the HIL test farm, from single-actuator benches to full-robot test cells, operating safely and unattended with high uptime.

• Build a hardware test signal engineers trust: per-PR reports, dashboards, and alerts, plus correlation of simulation and hardware results to surface sim-to-real gaps.

• Work with embedded, controls, ML, mechanical, and manufacturing teams to make testability a design requirement, and align with the Integration & Testing team in London on shared strategy and tooling.

What We're Looking For

• 5+ years in test automation, CI/CD, or test and integration engineering for hardware products such as robotics, automotive, aerospace, or drones.

• Experience building or scaling HIL or hardware-in-CI systems: rig design, test orchestration, device farms, or automated hardware regression.

• Strong Python and/or C++, and fluency with CI/CD tooling (like GitHub Actions), including self-hosted runners on physical hardware.

• Comfort at the hardware/software boundary: reading schematics, wiring a bench, debugging over CAN, EtherCAT, or serial, and scripting power supplies, DAQs, and instruments.

• Experience with Nvidia based embedded targets and firmware flashing workflows and bootloader recovery via JTAG.

• Experience with Linux based CLI systems.

• A practical approach to flaky tests and to keeping a hardware test signal trustworthy.

• Root cause analysis skills: telling a bad part from a bad assembly or a bad design.

Nice to have

• ROS/ROS 2, real-time control, actuator or motor testing, force-torque sensing, or locomotion and manipulation test design.

• Validating learned or RL policies on hardware, or sim-to-real work in Isaac Sim/Lab, MuJoCo, or Gazebo.

• NVIDIA or similar edge-compute deployment.

• Safety engineering exposure: functional safety, e-stop chains, ISO 10218 or ISO 13482.

• Test fixture design, or working with technicians and machine shops to build fixtures.

• Grafana, Prometheus, or custom telemetry pipelines for large test-log volumes.

Why this role matters

Every policy that walks and every gripper that closes on a customer's production line will have passed through the infrastructure you build. Few roles connect your work to robots operating safely in the real world this directly.

What We Offer

• Comprehensive health coverage for US‑based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources.

• Meaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays.

• 401(k) retirement plan with 4% employer match.

• Competitive equity: stock options with meaningful upside as we scale.

• Free daily catered lunch, snacks, and drinks in‑office.

• Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.

• Freedom to influence the product and own key initiatives.

For this role in California, the expected base salary range is $128K–$160K USD per year; your placement in that range depends on how your experience maps to our internal leveling.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role

As a Senior Platform Software Engineer at Humanoid, you will be at the heart of developing the core OS, data networks and protocols, and fundamental software subsystems for our next-generation humanoid robots. You will help develop the foundational software architectures that allow high fidelity robotic controls and AI development. You will be responsible for writing high-integrity software that runs on our robots, integrating sensors, safety systems, and computing platforms to enable safe human-robot collaboration.

In this role, you will have the opportunity to take full ownership of new systems and directly contribute to the development of our future products. If you are interested in complex embedded software projects, thrive in a fast-paced, collaborative environment, and want to make a real impact on the future of human-robot interaction, we want you on our team!

What You'll Do

• Design & Create Embedded Software: Develop and validate embedded software that ensures our robots can operate at scale in the real world.

• Hardware & Software Integration: Work at the intersection of hardware and software to integrate various robotic components (e.g., sensors, actuators, computing platforms) into a cohesive, fault-tolerant system.

• Lead Cross-Functional Projects: Lead interdisciplinary projects that involve robotic perception, computing subsystems, and software integration, collaborating with engineers across multiple domains.

• Test & Evaluate Systems: Integrate new systems with our robots to test, validate, and ensure that they meet safety requirements and perform reliably in real-world conditions.

• Build Infrastructure for Innovation: Contribute to the development of tools, infrastructure, and operational practices within a small, agile R&D team focused on unlocking new capabilities for Humanoid robots.

• Drive Safety in Robotics: Be part of a team working at the cutting edge of technology to improve the safety and performance of robots operating in real-world, human-centric environments.

• Collaborate Across Teams: Work closely with electrical engineers, software developers, robotics control experts, physical AI developers, and other team members to integrate software systems with robotics hardware, ensuring seamless operation and performance.

What We're Looking For

• 5+ years of experience developing and deploying production software in embedded systems running Linux (C++, C, Rust, Python, Go).

• Experience developing time-sensitive, performance critical applications.

• Thorough understanding of Ethernet and IP networking and higher-level protocols like HTTP or gRPC.

• Experience with Linux build environments like Yocto or Buildroot.

• Experience in building Linux kernels and modifying or writing device drivers.

• Experience with Nvidia’s Jetson platform is a plus.

• Experience working with sensor data, including cameras, lidars, radars, and IMUs is a plus.

• Strong communication skills, with the ability to write clear technical documentation and deliver presentations on complex topics.

• Proven history of leading cross-functional technical projects, including developing technical requirements and driving collaboration across teams.

• Experience working in small, agile teams with fast iteration cycles and interdisciplinary collaboration.

What We Offer

• Competitive equity: stock options with meaningful upside as we scale.

• 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).

• Private healthcare, including virtual and in-person care.

• Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in-office.

• Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.

• Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role

We’re looking for a Senior HR Operations Manager to play a key role in building and scaling the HR operations that support our growing team.

This is an opportunity to have real ownership and impact. You’ll oversee the core employee lifecycle while shaping the processes, systems, and ways of working that enable us to grow effectively. From improving existing workflows to introducing smarter, more automated solutions, you’ll have the freedom to challenge how things are done and make them better.

Working closely with HR Business Partners, Talent Acquisition, Payroll, Finance, and Legal, you’ll help create a seamless employee experience and ensure our HR operations are accurate, efficient, and built to scale.

If you enjoy bringing structure to fast-moving environments, solving operational challenges, and building things that make a tangible difference, this is a chance to help shape HR Operations at an exciting stage of our growth.

What You'll Do

• Own end-to-end HR operations: onboarding/offboarding, employee data management, contracts, and HRIS administration

• Design and continuously improve HR processes and workflows to support rapid headcount growth

• Partner with Payroll and Finance to ensure accurate, timely monthly payroll inputs (starters, leavers, changes, benefits)

• Partner with Legal, HR Business Partners and Talent Acquisition to ensure a smooth, well-documented employee lifecycle

• Act as the escalation point for employee queries relating to contracts, benefits, and policies

• Support audits (right-to-work, compliance, insurance) and maintain accurate employee records

• Ensure HR policies, employee handbooks, and processes comply with UK employment law (and monitor changes that require updates)

• Manage relationships with external vendors (such as benefits providers etc)

• Identify opportunities to automate and simplify recurring HR admin work

What We're Looking For

• 3+ years of experience in People Operations, ideally in a fast-growing or scale-up environment

• Solid working knowledge of UK employment law and best practice

• Experience owning or administering an HRIS (preferably HiBob)

• Experience coordinating with payroll providers and benefits administration in the UK

• Strong Excel/Google Sheets skills; comfortable working with and cleaning large datasets

• Excellent attention to detail and a process-first mindset

• Strong communication skills — able to explain policy and process clearly to employees at all levels

• Comfortable working in ambiguity and building processes from scratch where none exist yet

What We Offer

• Competitive equity: stock options with meaningful upside as we scale.

• 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).

• Private healthcare, including virtual and in-person care.

• Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in-office.

• Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.

• Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role

We're hiring a Senior/Staff Autonomy Engineer focused on Spatial Intelligence to join our team. In this role, you will bridge the gap between classical spatial geometry and next-generation AI. You will lead the design and development of robust state estimation, long-term mapping, and localisation loops, with a specific focus on integrating modern machine learning techniques and foundation geometry models into our core navigation stack. Your work will ensure our robots possess rock-solid spatial awareness and execute highly reliable trajectories over extended deployments in complex, real-world environments.

What You'll Do

• Architect the spatial intelligence layer that unifies 3D geometry with semantic scene understanding to ensure safe and efficient navigation and locomotion in complex environments

• Develop advanced 3D spatial reasoning capabilities that provide our robots with long-term persistent spatial memory and a deep contextual awareness of their surroundings.

• Own the entire perception lifecycle by training large-scale multimodal networks and deploying and integrating them for ultra-low latency performance on edge hardware

• Bridge the gap between conceptual research and physical reality by implementing state-of-the-art 3D representations that track and interpret the environment state

• Collaborate with cross-functional teams to bridge the gap between large-scale model training and reliable robot integration.

• Stay ahead of the field, rapidly evaluate new model architectures, benchmarks, and datasets to guide our embodied AI roadmap.

What We're Looking For

• Exceptional software engineering skills with a proven track record of shipping complex ML systems into production.

• Strong background in 3D scene understanding and the design of efficient spatial data structures.

• Deep experience in machine learning for vision or embodied AI, ideally with large models (VLMs, transformers, or multi-modal architectures).

• Proficiency in PyTorch and hands-on experience building, fine-tuning, and deploying large-scale ML systems.

• High-impact individual contributor capable of taking projects from conceptual research to high-performance robot code.

• Comfortable working in a fast-moving, research-driven environment with evolving models, data, and tools.

What We Offer

• Competitive equity: stock options with meaningful upside as we scale.

• 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).

• Private healthcare, including virtual and in-person care.

• Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in-office.

• Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.

• Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About The Role

We are looking for a Senior Control Engineer to join our Controls Team in Vancouver, focusing on SW control development and integration of robotic actuators and sensors.

You will be responsible for designing, implementing, and validating joint- and actuator-level controllers that deliver high precision, responsiveness, and safety for complex robotic mechanisms.

The ideal candidate has a solid background in control theory, strong software engineering skills in C++, and comfort working across the full stack from real-time embedded control up through networking, kinematics/dynamics, and browser-based debugging tooling. You will work closely with other control and hardware engineers to model, tune, and optimize the behavior of real robots and their subsystems (i.e. limbs and end-effectors).

What You’ll Do

Low-Level Control Development

• Tune and validate actuator - and joint-space control loops (PID, feedforward, impedance/admittance, observers, state feedback) for multi-DoF systems in ROS2.

• Work across EtherCAT/CAN and Linux networking (TCP/IP, DDS discovery, time sync) to ensure deterministic, safe real-time operation.

• Implement safety and fault-handling mechanisms for dynamic conditions.

Modeling, Kinematics & System Identification

• Build and identify models of actuators, transmissions, and mechanisms — including parallel mechanisms like differential wrists/ankles — for control design and simulation.

• Apply rigid body kinematics/dynamics and numerical IK/FK methods; work from URDF/Xacro and MJCF, interpreting mechanical drawings and geometry.

Software & Systems Integration

• Write real-time-safe, object-oriented C++ (lock-free structures, thread safety) for control and diagnostics.

• Design and debug multi-layer control architectures.

• Maintain CMake build/dependency tooling and Python test harnesses; build lightweight browser-based tools (HTML/JS/WebSocket) for hardware debugging.

Sensor & Hardware Integration

• Integrate and calibrate a range of sensors (F/T sensors, tactile sensors, IMUs, etc.) with real-time acquisition and processing across the control stack.

• Hands-on hardware bring-up and debugging.

Cross-Disciplinary Collaboration

• Close the loop with mechanical/electronics engineers across sites on actuation requirements;

• Support hardware bring-up, calibration, and performance testing.

What We're Looking For

• M.S. or Ph.D. in Control Engineering, Robotics, Mechanical Engineering, or Electrical Engineering with 5+ years in robotic or mechatronic systems — equivalent practical experience counts.

• Shipped real-time-safe, object-oriented C++ control software running on real hardware, in production or a serious research programme.

• Tuned and validated controllers on physical actuators, including sensor calibration and bring-up — with a story about something that behaved nothing like the model and what you did about it.

• Debugged at the fieldbus and OS layer: EtherCAT (PDO/SDO, timing constraints) or CAN, on an RTOS or real-time Linux.

• Strong control theory foundation (linear/nonlinear control, stability, observers, state estimation, feedback/feedforward, filtering, frequency-domain analysis) applied to multi-DoF mechanisms via Jacobians, numerical IK/FK, and URDF/Xacro.

Preferred Qualifications

• BLDC motor control (commutation, current control, torque optimization)

• ros2_control internals (hardware interfaces, controllers, controller_manager, plugins, lifecycle nodes).

• Parallel mechanisms specifically (differential wrist, parallel ankle), robotic hands, or other multi-DoF end-effectors.

• System identification toolchains and simulation environments (MATLAB/Simulink, MuJoCo, Gazebo); MJCF.

• Experience with dynamic system modeling and simulation at the actuator and transmission level.

What We Offer

• Comprehensive extended health benefits starting on your first day, including fully paid medical and dental, virtual care, employee and family assistance, and worldwide emergency medical support.

• Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays.

• Competitive equity: stock options with meaningful upside as we scale.

• Free daily catered lunch, snacks, and drinks in‑office.

• Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.

• Freedom to influence the product and own key initiatives.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the Role

We are looking for a strong Machine Learning Research Engineer to join our Autonomy team and develop the learning-based algorithms that power dynamic locomotion and whole-body control on our humanoid robots.

You will develop robust, reusable motion capabilities that enable the robot to move dynamically, maintain balance, interact with its environment, and combine locomotion with manipulation. This includes building the underlying learning-based motion primitives that can be composed into increasingly complex whole-body behaviors.

You will work closely with robotics, controls, simulation, and machine learning engineers to turn learned behaviors into reliable capabilities running as part of the robot's real-time control stack.

What You'll Do

• Design and train learning-based locomotion and whole-body control policies for dynamic robotic behaviors.

• Develop motion primitives using different learning based generative models.

• Apply reinforcement learning, imitation learning, and other learning-based approaches to motion generation and control.

• Build scalable simulation, data generation, and training pipelines using platforms such as Isaac Lab and MuJoCo.

• Develop methods for robustness, adaptation, and sim-to-real transfer, including domain randomization and learning from real-world robot data.

• Deploy, evaluate, debug, and fine-tune learned policies on physical humanoid robots.

• Optimize policy inference and training systems for the performance and latency requirements of real-time control.

• Integrate learned policies into the broader robot control and autonomy stack.

What We're Looking For

• BS, MS, or PhD in Robotics, Machine Learning, Computer Science, or a related technical field.

• 3+ years of experience developing machine learning systems in industry or research.

• Strong understanding of deep learning and modern policy architectures, including training, inference, experimentation, and debugging.

• Hands-on experience with RL and at least one additional area such as imitation learning, generative models, sequence models, or large-scale representation learning.

• Strong Python and PyTorch experience.

• Experience with physics-based simulation environments such as Isaac Lab, Isaac Sim, MuJoCo, or similar platforms.

• Ability to reason about learning algorithms in the context of dynamics, control, and physical systems.

Nice to have:

• Experience applying reinforcement learning or imitation learning to legged robots, humanoids, or other complex physical systems.

• Experience with whole-body control, locomotion, motion imitation, or loco-manipulation.

• Experience deploying learned policies on real robotic systems and debugging the sim-to-real gap.

• Familiarity with motion capture, trajectory optimization, model-based control, or learning from demonstrations.

• Experience training policies at scale across large numbers of simulated environments.

• Publications at NeurIPS, ICML, ICLR, CoRL, RSS, CVPR, or equivalent contributions to impactful open-source robotics or machine learning projects.

What We Offer

• Competitive equity: stock options with meaningful upside as we scale.

• 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).

• Private healthcare, including virtual and in-person care.

• Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in-office.

• Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.

• Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About the role:
At Humanoid, we are working from a simple hypothesis: AI is rapidly transforming engineering. The bottlenecks are shifting from writing code to how efficiently AI-authored changes can be verified.

We’re looking for a Technical Lead to build the platform that lets our engineers move faster with coding agents while protecting our code, infrastructure, and robots. You’ll give developers and agents the environments, context, and tools to work effectively, and build verification and security into the path from task to healthy deployment. This means rethinking how engineering work gets done, not just adding agents to existing processes and establishing the access controls, isolation, and monitoring needed to guard against mistakes, misuse, and new security threats.

This is a hands-on leadership role and the keystone hire for a new team. You’ll build the critical systems yourself, recruit and lead engineers, and work across Developer Tools, Security, Safety, Simulation, and robot software. Success means increasing engineering output while reducing cost and human review per accepted change, without increasing defects or safety risk.

What you'll do:

• Own the path from an agent task to a healthy deployed change, including acceptance criteria, execution, verification, merge, rollout, monitoring, and rollback.

• Build secure, reproducible agent runtimes with task-scoped identity, short-lived credentials, bounded access, cost controls, and re-playable execution records. Proactively detect unauthorized agent activity across our compute clusters, whether internal or external.

• Build the interfaces developers use to launch, monitor, and control agents, alongside tooling for agents to collaborate through shared memory, coordinated work, and appropriately authorized access to company resources.

• Reduce the tokens and retries required for accepted work through better context assembly, model and tool routing, caching, task decomposition, and feedback.

• Give agents fast access to builds, tests, simulation, replay, and hardware-in-the-loop, with acceptance criteria they cannot alter.

• Work with engineering teams to make the codebase easier to navigate and verify through clear interfaces, strong invariants, reproducible environments, fast local checks, and well-documented implementation paths.

• Recruit and lead the team while remaining hands-on. Measure success through cost per accepted change, human review time, escaped defects, and time from push to healthy on the robot.

What we're looking for:

• Experience building and operating developer tooling or infrastructure used across engineering teams, such as build systems, CI/CD, test infrastructure, deployment pipelines, or internal platforms.

• Strong software engineering skills and comfort working in large codebases or monorepos.

• Practical experience with Linux, containers, and cloud infrastructure, plus working knowledge of Kubernetes

• Hands-on experience using and integrating coding agents into real engineering workflows. You understand how context, tools, and evals affect reliability, latency, and cost, and can talk concretely about what worked and what didn’t.

• Sound security judgment around workload isolation, identity, permissions, and credentials. You can design appropriate boundaries for agents accessing code, infrastructure, and company resources.

• Experience building reliable automated tests or verification systems and diagnosing failures across code, tooling, and infrastructure. You have good judgment about what automated checks establish and where human review still matters.

• Experience leading engineers while remaining hands-on. You can set technical direction, recruit a strong team, and turn an ambitious goal into systems that engineers use and trust.

What We Offer:

• Competitive equity: stock options with meaningful upside as we scale.

• 30+ paid days off, including 23 days of annual leave, all UK bank holidays, and additional company closure days (including Christmas–New Year shutdown).

• Private healthcare, including virtual and in-person care.

• Pension scheme with 8% total contribution (5% employee, 3% employer) on full earnings.

• Free daily breakfast, catered lunch, and snacks in-office.

• Work at the frontier - collaborate daily with world-class engineers, researchers, and product experts building the next generation of AI and humanoid robotics.

• Real ownership - direct access to founding leadership, meaningful input on product direction, and the ability to drive key initiatives from day one.