СБЕР

Senior DS/LLM Engineer (ИИ‑агенты для бизнеса) (Python, FastAPI)

Центр практического искусственного интеллекта занимается разработкой и внедрением высокотехнологичных AI-инструментов. Задачи берутся из повседневной практики бизнеса.

СБЕР · На сервисе с: 13.08.26 17:45

↑ Вакансия с автоподнятием
Зарплата не указанаРоссияг МоскваГибрид

Центр практического искусственного интеллекта занимается разработкой и внедрением высокотехнологичных AI-инструментов. Задачи берутся из повседневной практики бизнеса.

Первый этап отбора на эту вакансию – общение с AI-рекрутером. После отклика ждите сообщение от него в мессенджере, диалог займёт примерно 10 минут. Задача AI-рекрутера — уточнить недостающие детали и ускорить рассмотрение вашей кандидатуры. AI-рекрутер только начинает свой путь, поэтому просим относиться с пониманием. Ваш опыт и участие помогут сделать его удобным и полезным для всех!

Задачи:

  • разработка и внедрение LLM-агентов и продвинутых RAG систем в управленческом домене для решения стратегических задач банка — от прототипов до продакшена
  • решение прикладных задач оценки качества и полноты предоставленной документации/отчетности в бизнес доменах средствами ИИ-ассистентов (RAG-пайплайны, классификация запросов, генерация ответов, оценка релевантности)
  • исследование и настройка multi-agent orchestration (LangGraph, LangChain, schema guided reasoning pipelines)
  • работа с GigaChat как основной моделью, а также эксперименты с ChatGPT, Gemini, Qwen
  • fine-tuning моделей (instruction-tuning, adapters, LoRA, SFT, LLM-RL)
  • разработка метрик качества
  • взаимодействие с инженерами и аналитиками — внедрение моделей в реальные кейсы.

Требования:

  • опыт в роли DS/ML от 3 лет
  • глубокая экспертиза в NLP/LLM
  • уверенное знание инструментов разработки и инфраструктуры (bash, docker/openshift, git и т.д.)
  • фундаментальные знания в сфере ML, профильное образование
  • отличные знания языка Python и опыт индустриальной разработки
  • понимание архитектуры LLM и принципов prompt engineering
  • опыт построения RAG-систем, fine-tuning и дообучения моделей
  • умение проектировать пайплайны inference / retraining
  • опыт упаковки моделей в сервисы и интерфейсы (например, FastAPI, Flask, Tornado, StreamLit, ChainLit и т.д.)
  • опыт интеграции LLM с внешними API или базами знаний.

Мы предлагаем:

  • комфортный современный офис г. Москва, рядом с метро Кутузовская
  • офисный формат работы (возможно обсудить гибрид после исп.срока)
  • ежегодный пересмотр зарплаты и годовая премия
  • корпоративный спортзал и зоны отдыха
  • более 400 образовательных программ СберУниверситета для профессионального и карьерного развития
  • расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа
  • гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ
  • подписка Прайм с возможностью совместного использования на трёх близких
  • вознаграждение за рекомендацию друзей в команду Сбера.

Похожие вакансии AI инженер

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Н

Senior ML / AI Engineer

Неизвестный работодательНа сервисе с: 04.10.26 13:17
4 000–7 000 € (≈ 377k–660k ₽)КипрLimassolОфис

#вакансия #кипр #офис #ML #AI #инженер

**Senior ML / AI Engineer**
Лимасол, Кипр

**Обязанности:**
- Владение задачами, а не только моделями. Совместно с менеджером продукта превращать цели в решения.
- Работа с LLM: проектирование контекста, извлечение данных, использование инструментов и агентных потоков.
- Обучение собственных моделей: модерация, классификация, распознавание и обнаружение аномалий.
- Принятие решений о создании или покупке: оценка качества, задержки и затраты.
- Вывод моделей в продакшн: работа под нагрузкой, мониторинг и откат.

**Требования:**
- Опыт работы с LLM в продакшне, включая извлечение и адаптацию моделей.
- Умение обучать собственные модели на реальных данных.
- Опыт работы в продакшн-инжиниринге не менее 5 лет, знание Python и PyTorch.
- Английский на уровне Intermediate и выше.

**Зарплата:** €4 000–7 000 gross в месяц

Если это звучит интересно — напишите мне ••••••••

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T

Senior Machine Learning Engineer

tolokaНа сервисе с: 03.10.26 19:22↑ Вакансия с автоподнятием
Зарплата не указанаЕвропаПольшаКипрВеликобританияГерманияНидерландыИспанияПортугалияСербияЧехияЛюксембургМолдоваЛатвияЧерногорияЛитваШвейцарияЭстонияВенгрияИсландияНорвегияРумынияФинляндияФранцияАвстрияГрецияДанияИталияСловакияУдалёнка

About Toloka

At Toloka AI we create data that powers leading GenAI models and innovations. We work with frontier labs, big tech, renowned AI startups, enterprises and non-profit research organizations worldwide. We use a combination of Experts + Crowd + Tech Platform to teach AI models to reason and evaluate their efficacy and safety. We have experts in more than 50 different domains—from doctors and lawyers to physicists and engineers—and boast one of the most diverse global crowds, representing over 100 countries and speaking 40+ languages. We are a well-funded startup with an enviable portfolio of clients including Anthropic, Amazon, Microsoft, Poolside, Recraft, and Shopify.

Recently, we secured strategic investment led by Bezos Expeditions and Nebius Group with participation from Mikhail Parakhin, CTO of Shopify and board advisor to leading GenAI companies, who now serves as our Chairman of the Board. Our remote-first team is globally distributed around the world: USA, UK, the Netherlands, Serbia, and more.

 

About the Team

We are the ML team inside Toloka — we build the machine-learning products that power the platform itself, so every project running on Toloka is faster, cheaper, and more reliable.

A few examples of what we own:

  • LLM QA — the core technology behind Toloka's automated quality-check mechanism. Every annotation flowing through Self-Service is reviewed by an LLM agent we design, train, and operate.
  • Model distillation and fine-tuning — adapting frontier and open-source models to Toloka's tasks to hit the right quality at the right cost.
  • Evaluation, benchmarking, cost modeling, and model selection across providers.

We own the full chain. The same team designs the ML solution, ships it to production, keeps it running 24/7, analyzes the results coming back from real projects, and feeds that signal into the next iteration. No hand-off between research, engineering, and operations — it's all us.

 

About the Position

As a Senior ML Engineer, you will design, train, and deploy the AI agents that drive our core products. You will focus on end-to-end ML tasks—including fine-tuning and Reinforcement Learning (RL)—to build resilient agentic workflows in Python. You will own the full lifecycle of your models, closing the loop from research and benchmarking to production scaling and monitoring.

 

What you’ll do

  • Train, fine-tune, and distill ML models (including RL approaches) to power autonomous AI agents.
  • Build and operate agentic workflows in Python, handling complex reasoning and hybrid human-expert interactions.
  • Own evaluation and benchmarking, selecting foundational models and establishing cost models.
  • Manage the full ML lifecycle: design solutions, ship to production, and monitor real-time signals.
  • Implement observability metrics tailored for agent logic, model performance, and system reliability.

 

What we're looking for

  • 3+ years of experience in ML: Strong background in model training, fine-tuning, and Reinforcement Learning (RL);
  • 1+ year in Agent Development: Practical experience building, evaluating, and launching autonomous AI agents;
  • Agentic Frameworks: Proven experience working with frameworks such as LangChain, LlamaIndex, or AutoGen;
  • Open-Source LLMs: Practical knowledge of model distillation and adapting open-source models (e.g., Llama, Mistral);
  • Python Mastery: Advanced proficiency in Python with a drive to apply disciplined software engineering standards to ML;
  • End-to-End Ownership: Ability to work across the entire chain, from research to production operations;
  • Language: Fluency in English (B2 or above).

 

What we can offer

  • You will be part of an international, dynamic environment that drives innovation and sets new standards in the AI and technology sector.
  • Competitive compensation package including base salary, bonus, and ESOP.
  • Paid PTO and benefits will vary depending on location.
  • We offer a full remote or hybrid model (if you are based in NL or Serbia).
  • IT setup and home office allowances.

 

Equal Opportunity Employer:

Toloka is committed to providing equal opportunity and fostering an inclusive environment. We welcome applications from all qualified individuals and do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, gender identity, age, marital status, veteran status, disability, or any other characteristic protected by applicable law. Selection decisions are made based on qualifications, merit, and business need.

 

[Important Notice] Scam Alert Regarding Fake Job Postings

It has come to our attention that an individual or group is fraudulently impersonating Toloka to post fake jobs and solicit personal information from applicants. Please be aware:

  • Official Communication: Our recruiting team will only contact you from an official "toloka.ai" email address. We will NEVER use Gmail, Yahoo, Tolokainc, toloka.inc, or other personal or seemingly business email accounts.
  • Our Process: We will never ask for your bank account details, credit card number, or any fees as part of the application or interview process.
  • Official Listings: All legitimate job openings are posted on our official careers page: https://toloka.ai/careers#job-list

What to do: If you see a suspicious job posting or have been contacted by someone you suspect is a scammer, please do not provide any personal information. Instead, report the incident to us directly at security@toloka.ai and report the profile/post to LinkedIn.We are taking this matter very seriously and are working with the appropriate parties to resolve it.

Thank you for your vigilance!

To learn how we collect, use, disclose, and store personal data, check out our Privacy Notice.

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T

Freelance Forward Deployed AI Engineer

tolokaНа сервисе с: 03.10.26 19:04↑ Вакансия с автоподнятием
Зарплата не указанаСШАУдалёнка

Company Intro

At Toloka AI we create data that powers leading GenAI models and innovations. We work with frontier labs, big tech, renowned AI startups, enterprises and non-profit research organizations worldwide. We use a combination of Experts + Crowd + Tech Platform to teach AI models to reason and evaluate their efficacy and safety. We have experts in more than 50 different domains—from doctors and lawyers to physicists and engineers—and boast one of the most diverse global crowds, representing over 100 countries and speaking 40+ languages. We are a well-funded startup with an enviable portfolio of clients including Anthropic, Amazon, Microsoft, Poolside, Recraft,  and Shopify.

Recently, we secured strategic investment led by Bezos Expeditions and Nebius Group with participation from Mikhail Parakhin, CTO of Shopify  and board advisor to leading GenAI companies, who now serves as our Chairman of the Board. Our remote-first team is globally distributed around the world: USA, UK, the Netherlands,  Serbia, and more. 

About position

The Forward Deployed AI Engineer is Toloka's most senior client-facing technical role. You will partner directly with CTOs, VPs of Engineering and ML, research leaders, and applied AI teams, helping them solve complex AI data challenges and translate ambitious model goals into practical, scalable solutions.

This is a hands-on role. You will design and build the data-generation, labeling, and evaluation pipelines that power the next generation of AI models. Rather than training the models yourself, you'll help clients identify the right data strategy and own the solution from problem discovery through implementation and delivery.

Beyond delivering client solutions, you'll help shape how Toloka approaches AI solution engineering - establishing best practices, raising the technical bar across engagements, and mentoring Solution Engineers and Technical Consultants.

Why this role is different

Every engagement is different. One week you might be designing evaluation pipelines for frontier foundation models, the next helping an enterprise build domain-specific reasoning datasets or synthetic data workflows.

This role sits at the intersection of consulting, engineering, and AI. You'll work directly with some of the world's leading AI companies, helping shape how next-generation models are trained and evaluated.


What you'll do

Executive partnership

  • Act as the primary technical counterpart to CTOs, VPs of Engineering, and research/engineering leadership.
  • Lead executive conversations using a structured, answer-first (BLUF) approach.
  • Manage escalations and expectations with composure and integrity.
  • Build long-term trusted relationships by recommending evidence-based solutions.

Data strategy & needs diagnosis

  • Ask excellent questions to uncover the client's real need - the "question behind the question." Understand their model, which metrics they want to move, and how they intend to train or evaluate it.
  • Draw on a solid understanding of how LLMs are trained and fine-tuned to have credible conversations with their technical leaders, understand their data strategy, and proactively propose the data that will solve their problem - with options and rationale ("based on your goal, you likely need this, or this").

Solution engineering & delivery (hands-on)

  • Design and build the data solutions yourself: configure data-labeling components and quality controls, develop user interfaces and AI-driven solutions (e.g. agentic systems, RAG, synthetic data generation), and integrate them into automated, multi-stage pipelines that produce data for AI training and evaluation.
  • Architect and reason about complex, multi-stage solutions end to end; run experiments to prove the pipeline delivers data of the required quality and speed; iterate from MVP toward production.
  • Provide technical leadership across multiple client engagements, establish reusable engineering standards and best practices, and mentor Solution Engineers and Technical Consultants to raise the overall technical bar of the organization.

Commercial ownership

  • Own delivery end to end - timelines, quality, and scalability - and the commercial outcome: Gross Margin and Contribution Margin, with the levers, trade-offs, and next checkpoints named, not just described.
  • Identify and drive expansion opportunities.

About You

No one is expected to meet every requirement below. If you bring a strong combination of client-facing communication, AI/LLM expertise, and hands-on engineering experience, we'd love to hear from you.

  • Executive communication. You can confidently lead conversations with CTOs, VPs, and senior technical stakeholders - clear, concise, structured, persuasive, and calm under pressure. Professional English (C1+) is essential.
  • Strong understanding of modern LLM development. You understand how modern LLMs are trained, fine-tuned, and evaluated (including SFT, RLHF/RLAIF, DPO/PPO, reward modeling, and LoRA/PEFT). You're comfortable discussing these topics with senior technical stakeholders and translating their goals into effective AI data solutions.
  • Hands-on solution engineering. You've designed complex AI solutions, built multi-stage pipelines, and developed AI-driven systems (e.g. agentic workflows, RAG, or synthetic data generation). You're comfortable working in Python (NumPy, Pandas), integrating APIs, and independently prototyping LLM-powered solutions.
  • Solid software engineering foundations. You understand version control, testing, MVP thinking, and iterative development. Experience building production software is a strong plus.
  • Exceptional discovery and problem framing. You enjoy working through ambiguity, asking the right questions, and translating business or research goals into clear AI data and evaluation strategies.
  • Seniority and track record. 8+ years delivering complex AI, ML, or data projects end to end, with experience influencing technical direction beyond individual projects. Experience establishing engineering standards, mentoring engineers, or leading cross-functional technical initiatives is highly valued. Experience in top-tier strategy consulting (McKinsey, Bain, BCG) and/or as an applied ML / LLM engineer is a strong advantage.
  • Ownership mindset. You take responsibility for outcomes, make thoughtful trade-offs between time, cost, and quality, and are comfortable owning both technical and commercial success.

Nice to have

  • Hands-on experience training or fine-tuning LLMs and/or building agentic systems (helps you reason about client needs - though the role itself is about building data solutions, not training models).
  • Advanced degree (MSc/PhD) in AI, CS, or a related field.
  • Experience in crowdsourcing and/or data-centric AI, and with fast-paced, multi-project delivery for frontier AI clients.

What we can offer

  • Freelance (B2B) collaboration, with a path into a project team if things go well;
  • Flexible, fully remote schedule (40 hours per week);
  • Work at the leading edge of AI development, alongside a dedicated and dynamic team of experts;
  • Projects with customers that are AI industry leaders and well-known household names;
  • Friendly community.


[Important Notice] Scam Alert Regarding Fake Job Postings

It has come to our attention that an individual or group is fraudulently impersonating Toloka to post fake jobs and solicit personal information from applicants.Please be aware:

  • Official Communication: Our recruiting team will only contact you from an official "toloka.ai" email address. We will NEVER use Gmail, Yahoo, Tolokainc, toloka.inc,  or other personal or seemingly business email accounts.
  • Our Process: We will never ask for your bank account details, credit card number, or any fees as part of the application or interview process.
  • Official Listings: All legitimate job openings are posted on our official careers page: https://toloka.ai/careers#job-list
What to do: If you see a suspicious job posting or have been contacted by someone you suspect is a scammer, please do not provide any personal information. Instead, report the incident to us directly at security@toloka.ai and report the profile/post to LinkedIn.We are taking this matter very seriously and are working with the appropriate parties to resolve it.

Thank you for your vigilance!

To learn how we collect, use, disclose, and store personal data, check out our Privacy Notice.

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