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Why work at Nebius
Nebius 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 work
Headquartered 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 800 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.
This role is for Nebius AI R&D, a team focused on applied research and the development of AI-heavy products. Examples of applied research that we have recently published include:
- investigating how test-time guided search can be used to build more powerful agents;
- dramatically scaling task data collection to power reinforcement learning for SWE agents;
- maximizing efficiency of LLM training on agentic trajectories.
One example of an AI product that we are deeply involved in is Nebius AI Studio — an inference and fine-tuning platform for AI models.
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.
- Ensuring that infrastructure for running models on agentic tasks is robust and performant
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
- Reasonable understanding of performance aspects of large neural network training (sharding strategies, custom kernels, hardware features etc.)
- Strong software engineering skills (we mostly use python)
- Deep experience with modern deep learning frameworks (we use jax)
- Proficiency in contemporary software engineering approaches, including CI/CD, version control and unit testing
- Strong communication and leadership abilities
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 MHA, 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
What we offer
- Competitive salary and comprehensive benefits package.
- Opportunities for professional growth within Nebius.
- Hybrid 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!
