ML engineer in AI research

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.

• 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

• 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
• Будет плюсом: 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

• Competitive compensation
• Career growth and learning opportunities
• Flexibility and ownership
• Collaborative and innovative culture
• Opportunity to work on impactful AI projects
• International environment and talented teams
• Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI