- Страна
- Нидерланды
Откликайтесь
на вакансии с ИИ

Senior ML Engineer (AI Research)
Исключительная возможность для ML-инженера работать в R&D подразделении крупной международной компании. Высокий балл обусловлен сложностью задач, использованием передового стека (JAX) и возможностью публикации научных результатов.
Сложность вакансии
Роль требует глубоких знаний в области Reinforcement Learning и опыта работы с распределенным обучением LLM. Использование JAX и фокус на передовых исследованиях (guided search, reasoning) делают позицию крайне сложной и подходящей только для экспертов.
Анализ зарплаты
Компания предлагает конкурентную зарплату, соответствующую уровню Senior/Staff в Европе. Указанный рыночный диапазон отражает специфику AI Research, где компенсации выше средних по рынку разработки ПО.
Сопроводительное письмо
I am writing to express my strong interest in the Senior ML Engineer position within the AI R&D team at Nebius. With a deep background in training large-scale models and a passion for applied research, I have closely followed Nebius's recent work in reinforcement learning for SWE agents and long-context scenarios. My experience in scaling model training across multiple nodes and my proficiency with JAX align perfectly with your technical stack and the ambitious goals of your research team.
In my previous roles, I have successfully designed and executed complex ML experiments, focusing on guided generation and post-training optimization. I am particularly excited about the prospect of working on web-scale data collection and RL for reasoning models. I am confident that my blend of strong software engineering skills and theoretical depth in deep learning will allow me to contribute significantly to Nebius's mission of transforming the global AI economy.
Составьте идеальное письмо к вакансии с ИИ-агентом

Откликнитесь в nebius уже сейчас
Присоединяйтесь к команде Nebius и создавайте будущее AI-агентов на острие современных технологий!
Описание вакансии
Why work at NebiusNebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.
Where we workHeadquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 1400 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.
The role
This role is for Nebius AI R&D, a team focused on applied research in AI. Examples of applied research that we have recently published include:
- applying reinforcement learning for agent training in long-context multi-turn scenarios
- dramatically scaling task data collection to power reinforcement learning for SWE agents
- building a decontaminated evaluation for SWE agents that is regularly updated
- investigating how test-time guided search can be used to build more powerful agents
The results often lead to collaboration with adjacent teams where our research findings are applied in practice.
We are currently looking for senior- and staff-level ML engineers to work on research in areas such as:
- Guided search and reinforcement learning for agentic systems
- Reinforcement learning for reasoning models
- Web-scale problem collection for training agents
- Efficient model distillation
Some examples of what your responsibilities might include are:
- Conducting experiments to figure out efficient ways to train a large language model on traces of interactions with various environments
- Exploring methods of guided generation and search in the trajectory space
- Coming up with ways to mine relevant data at web scale and figuring out efficient ways to use this data in model post-training
- Conducting experiments with different reinforcement learning configurations in verifiable domains
- Exploring methods to train AI agents on tasks with non-verifiable reward signals
We expect you to have:
- A profound understanding of theoretical foundations of machine learning and reinforcement learning
- Deep expertise in modern deep learning for language processing and generation
- Substantial experience with training large models on multiple computational nodes
- Strong software engineering skills (we mostly use python)
- Deep experience with modern deep learning frameworks (we use jax)
- Strong communication and leadership abilities
- Experience designing, executing, and analyzing machine learning experiments with proper statistical rigor
- Ability to formulate research questions, design experiments to test hypotheses, and draw meaningful conclusions from results
- Ability to document research findings clearly and contribute to technical publications or report
Nice to have:
- Experience with deep reinforcement learning for LLMs, including techniques such as reward modeling, DPO, PPO etc
- Familiarity with important ideas in LLM space, such as RoPE, ZeRO/FSDP, Flash Attention, quantization
- Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field Master’s or PhD preferred
- Track record of building and delivering products (not necessarily ML-related) in a dynamic startup-like environment
- Experience in engineering complex systems, such as large distributed data processing systems or high-load web services
- Open-source projects that showcase your engineering prowess
- Excellent command of the English language, alongside superior writing, articulation, and communication skills
- Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing
What we offer
- Competitive salary and comprehensive benefits package.
- Opportunities for professional growth within Nebius.
- Flexible working arrangements.
- A dynamic and collaborative work environment that values initiative and innovation.
We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!
Создайте идеальное резюме с помощью ИИ-агента

Навыки
- Python
- JAX
- Reinforcement Learning
- Large Language Models
- Deep Learning
- Distributed Computing
- PyTorch
- CI/CD
- Unit Testing
- Machine Learning Research
Возможные вопросы на собеседовании
Позиция предполагает работу над сложными системами рассуждений и агентами.
Расскажите о вашем опыте внедрения алгоритмов RL (PPO, DPO) для дообучения языковых моделей: с какими основными трудностями вы сталкивались?
В описании указано использование JAX и обучение на множестве узлов.
Какие стратегии параллелизма (Data, Pipeline, Tensor parallelism) вы бы выбрали для обучения модели с 70B+ параметрами в среде JAX?
Одна из задач — сбор данных в масштабе веба.
Как вы подходите к вопросу деконтаминации (очистки) данных при сборе обучающих выборок из открытых источников для SWE-агентов?
Вакансия требует навыков проведения строгих экспериментов.
Как вы обеспечиваете статистическую значимость результатов при сравнении различных конфигураций RL в условиях ограниченных вычислительных ресурсов?
Упоминается работа с невалидируемыми сигналами вознаграждения.
Какие подходы вы бы предложили для обучения агентов в доменах, где невозможно автоматически проверить правильность ответа (non-verifiable rewards)?
Похожие вакансии
Middle, Middle+, Senior GenAI/LLM Разработчик
Middle / Senior GenAI Engineer (CV)
Senior / Lead LLM Engineer
Senior Computer Vision Engineer
AI Platform Engineer (RAG/Agents/Skills)
GenAI Engineer (LLMs · RAG · ML Systems) — Senior
1000+ офферов получено
Устали искать работу? Мы найдём её за вас
Quick Offer улучшит ваше резюме, подберёт лучшие вакансии и откликнется за вас. Результат — в 3 раза больше приглашений на собеседования и никакой рутины!
- Страна
- Нидерланды