Software Engineer, RL Environments

Job summary

San Francisco, CA · On-site · Full-time Compensation: $180,000–$220,000 + competitive equity ABOUT THE COMPANY An early-stage (post–Series A) company building the training data and evaluation infrastructure that frontier AI labs use to improve their models — designing high-signal datasets and running rigorous evaluations that go beyond static benchmarks.

Benefits

Qualifications

• 1–4 years of software engineering experience with strong technical depth
• Design targeted data slices that surface model failure modes across high-stakes domains (finance, code generation, enterprise workflows)
• Build and iterate on evaluation rubrics and reward signals powering RLHF and RLVR training pipelines
• Develop quantitative frameworks to measure dataset quality, diversity, and downstream impact on model alignment and capability
• Own end-to-end real world and synthetic data pipelines, from scoping with research teams to production-ready evaluation specs
• Run annotator modeling experiments to improve model capabilities across task types
• GREEN FLAGS
• Experience at RL environment companies
• Background in AI safety or benchmarking organizations like METR or Artificial Analysis
• Genuine obsession with how data structure, selection, and quality drive model behavior
• Ability to design lightweight experiments and move fast
• Former founders or early engineers at early stage startups

Responsibilities

• What you'll be doing

Degrees

Industry

Company size

Contract length