Senior ML Engineer (AI Research)

The role is for Nebius AI R&D, a team focused on applied research in AI. Examples of applied research include reinforcement learning for agent training in long-context multi-turn scenarios, scaling task data collection for RL in SWE agents, and building a decontaminated evaluation for SWE agents that is regularly updated. We are currently looking for senior- and staff-level ML engineers to work on research 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. Responsibilities may include conducting experiments to train a large language model on traces of interactions with various environments, exploring methods of guided generation and search in the trajectory space, mining relevant data at web scale and applying 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. Nice-to-have: deep RL for LLMs, RoPE, ZeRO/FSDP, Flash Attention, and a Bachelor’s degree in CS/AI/Data Science or related field; Master’s or PhD preferred.

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