Senior ML Engineer (AI Research)

About this role

Responsibilities

• 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

About Nebius Group

Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.