# Senior/Staff ML Engineer - AI R&D
Nebius is seeking senior- and staff-level ML engineers to work on applied research in AI, focusing on:
- Guided search and reinforcement learning for agentic systems
- Reinforcement learning for reasoning models
- Web-scale problem collection for training agents
- Efficient model distillation
## Key Responsibilities
- Conduct experiments to figure out efficient ways to train large language models on traces of interactions with various environments
- Explore methods of guided generation and search in the trajectory space
- Mine relevant data at web scale and figure out efficient ways to use this data in model post-training
- Conduct experiments with different reinforcement learning configurations in verifiable domains
- Explore methods to train AI agents on tasks with non-verifiable reward signals
- Design, execute, and analyze machine learning experiments with proper statistical rigor
- Formulate research questions, design experiments to test hypotheses, and draw meaningful conclusions
- Document research findings clearly and contribute to technical publications
## Required Experience
- 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 (Python)
- Deep experience with modern deep learning frameworks (JAX)
- Strong communication and leadership abilities
- Experience designing, executing, and analyzing machine learning experiments
- Ability to formulate research questions and draw meaningful conclusions
## Nice to Have
- Experience with deep reinforcement learning for LLMs (reward modeling, DPO, PPO)
- Familiarity with RoPE, ZeRO/FSDP, Flash Attention, quantization
- Bachelor's degree in Computer Science, AI, Data Science, or related field (Master's or PhD preferred)
- Track record of building and delivering products in startup-like environments
- Experience engineering complex systems (distributed data processing, high-load web services)
- Open-source projects showcasing engineering prowess
- Proficiency in CI/CD, version control, and unit testing