Research Engineer, RL Scaling Science

Highlights

• Study how RL scales across model size, compute, and task horizon.
• Ship validated RL findings directly into frontier model training.
• Build benchmarks that make long-horizon RL progress measurable.

What they offer

• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours

Ideal candidate

Empirical researcher who thrives at the research-engineering boundary, owning open-ended experiments end-to-end and turning rigorous results into real frontier models, motivated by safe beneficial AI.

Requirements

• Strong empirical research skills in Reinforcement Learning, large-scale ML training, or a closely adjacent area
• Demonstrated ability to own large experiments end-to-end, from design through interpretation
• Proficiency in Python and experience working with large-scale or distributed ML systems
• Comfort operating at the research/systems boundary, including debugging where the two meet
• Care about the societal impacts of AI and responsible scaling