Research Engineer - Environments, Data and Post-Training

Highlights

• Run post-training and RLVR experiments shaping rewards for frontier LLMs.
• Build scalable synthetic data pipelines powering agentic tool-use and reasoning.
• Design rubrics and evaluation systems guiding training at massive scale.

What they offer

• Bi-annual performance bonus structure
• Generous equity grant vested over 4 years
• Up to $15k relocation bonus
• $10K housing bonus if within 0.5 miles of office
• $1.5K monthly stipend for meals
• Free Equinox membership
• $200 monthly laundry reimbursement
• $200 monthly personal wellness reimbursement
• Health, Dental, Vision insurance

Ideal candidate

Applied researcher-engineer who thrives in fast, high-ownership experimentation. Obsessed with model behavior and data quality and excited to push frontier LLMs forward in person.

Requirements

• Strong applied research background with focus on post-training and/or model evaluation
• Strong coding proficiency and hands-on experience with machine learning models
• Strong understanding of data structures, algorithms, backend systems and engineering fundamentals
• Familiarity with APIs, SQL/NoSQL databases, and cloud platforms
• Ability to reason deeply about model behavior, experimental results, and data quality
• Excitement to work in person in San Francisco 5 days a week in high-intensity environment