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
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