9 months ago
Remote, Worldwide +2 moreSenior / Staff+
Responsibilities
- Conduct experiments on efficient training of large language models using interaction traces from varied environments.
- Explore guided generation and search methods in trajectory spaces.
- Develop web-scale methods for mining relevant data and using it efficiently in model post-training.
- Experiment with reinforcement learning configurations in verifiable domains.
- Investigate methods for training AI agents on tasks with non-verifiable reward signals.
- Design, execute, and analyze machine learning experiments with statistical rigor.
- Document research findings and contribute to technical publications or reports.
- Collaborate with adjacent teams to apply research findings in practice.
Requirements
- Profound understanding of theoretical machine learning and reinforcement learning foundations.
- Deep expertise in modern deep learning for language processing and generation.
- Substantial experience training large models across multiple computational nodes.
- Strong software engineering skills, primarily using Python.
- Deep experience with modern deep learning frameworks, particularly JAX.
- Experience designing, executing, and statistically analyzing machine learning experiments.
- Ability to formulate research questions, test hypotheses through experiments, and draw meaningful conclusions.
- Ability to document research findings clearly and contribute to technical publications or reports.
- Experience with deep reinforcement learning for large language models, including reward modeling, DPO, or PPO, is preferred.
- Familiarity with RoPE, ZeRO/FSDP, Flash Attention, and quantization is preferred.
- A bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field is preferred; a master’s degree or PhD is further preferred.
- Experience delivering products in a dynamic startup-like environment is preferred.
- Experience engineering complex distributed data processing systems or high-load web services is preferred.
- Open-source projects demonstrating engineering ability are preferred.
- Strong English-language, writing, articulation, communication, and leadership abilities.
- Proficiency with contemporary software engineering practices, including CI/CD, version control, and unit testing.
Benefits
- Comprehensive benefits package
- Flexible working arrangements
- Professional growth opportunities
- Collaborative work environment
Tech Stack
Categories
AI ResearchML Engineering
About Nebius
The Nebius AI Cloud brings powerful full-stack infrastructure for AI developers and practitioners across startups, enterprises and science institutes to build and deploy generative AI applications and rapidly deliver scientific breakthroughs by training and running ML models within a secure, high-performance, and cost-optimized cloud environment.