Member of Technical Staff RL Research and Environments

You will build datasets, evaluation frameworks, reward signals, and training environments for post-training. You will run experiments across data and reward designs, improve pipeline reliability and observability, and turn capability goals into measurable iteration cycles.

Responsibilities

• Design and build post-training datasets using synthetic generation, targeted data collection, and self-play
• Implement filtering, scoring, and mixture strategies for RL and post-training corpora
• Build and maintain evaluation frameworks that surface long-context failure modes
• Design reward signals and training environments for targeted capability improvements
• Run ablations across data sources, reward designs, and long-horizon task structures
• Improve the reliability and observability of post-training data and environment pipelines
• Collaborate with Product and Research to translate capability goals into measurable iteration cycles

Requirements

• Strong software engineering fundamentals
• Experience building or operating large-scale data or ML systems
• Ability to design and interpret experiments that measure model behavior changes
• Knowledge of ML, data systems, and infrastructure
• Attention to data quality and evaluation rigor
• Track record of owning experimental or production systems end-to-end

Benefits

• Equity as a significant part of total compensation
• 401(k) plan with 6% salary matching
• Health, dental, and vision insurance for employees and dependents
• Unlimited paid time off
• Visa sponsorship
• Relocation stipend to San Francisco