The role is working within our studio: Tripledot Games

About Tripledot Games

Tripledot Games is a leading developer and publisher of casual and puzzle games, with a strong presence in London, Warsaw, and Barcelona. The studio is responsible for multiple top 10 titles, including Woodoku, Woodoku Blast, Solitaire, and TripleTile. Our best-in-class data-driven approach spans the entire lifecycle from publishing to machine learning puzzle levels, helping us make fast, smart decisions at every stage of development.

We are also one of the largest IAA operators worldwide. Tripledot Games is a diverse and collaborative studio, home to people from over 36 nationalities. We take pride in our craftsmanship, strong focus on outcomes, and continuous improvement, building high-quality, scalable games that players around the world love.

Role Overview

Skills, Knowledge and Expertise

Working at Tripledot

At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the world’s most robust and effective developer tools. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

We are working on an ambitious new platform that provides AI capabilities to all JetBrains products. Our platform is based on models developed in-house for writing and coding assistance, as well as integration with our strategic partners.

We are looking for a Research Engineer who can contribute to training foundation models for coding tasks. You’ll be working on developing Large Language Models from scratch and deploying them into production environments where they will be accessible by end users across the globe.

We value engineers who: 

• Can plan projects and make decisions independently, consulting with others if needed.
• Identify customer needs and prioritize their tasks accordingly.
• Start with the simplest solutions and gradually add complexity as needed.
• Take sole responsibility for an entire subsystem.
• Have a passion for learning and a desire to stay up to date with the latest developments in the LLM field.

In this role, you will: 

• Work with stakeholders to convert business requirements into technical specifications.
• Train LLMs from scratch on a large GPU cluster.
• Collect and process pre-training and fine-tuning datasets.
• Support and improve existing subsystems.

We’ll be happy to have you on our team if you have: 

• Experience in design, deployment, and support of production ML systems.
• A strong theoretical background in NLP and transformer-based approaches.
• Proficiency with modern deep learning frameworks such as PyTorch and common libraries for NLP.
• Experience in distributed training of multi-billion parameter models.
• Attention to detail in everything you do and great communication skills.

We’d be especially thrilled if you have experience with: 

• LLM inference frameworks such as vLLM, DeepSpeed, TensorRT.
• LLM alignment techniques such as RLHF/RLAIF.
• MLOps tools and practices, including CI/CD for ML.
• K8s and Kubeflow.
• Scientific publications in the NLP field.

How we develop JetBrains AI: 

• A cluster of hundreds of NVIDIA GPUs as training infrastructure.
• Git for source control management.
• Python, PyTorch, and HuggingFace as an ML stack.
• Kubeflow and Weights & Biases for experiment tracking.
• TeamCity as a CI Automation system.

#LI-KP1

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.