Member of Technical Staff - Research & Post-training

Preference Model is seeking a Research Engineer or Scientist to advance the field of self-directed learning in large language models. This role involves implementing novel approaches, shaping research directions, and training/evaluating models on proprietary RL environments. You will architect and optimize RL training infrastructure, design training methodologies, and profile/optimize training runs for efficiency.

• Train and evaluate models on proprietary RL environments
• Architect and optimize RL training infrastructure
• Design, implement, and test RL training environments and methodologies
• Profile and optimize training runs for throughput and iteration speed
• Experience running end-to-end LLM post-training pipelines (7B+ models)
• Proficiency in Python and PyTorch or JAX