Research Engineer

San Francisco Data turns production traces into training environments for frontier models. We've reached $100M+ in annualized revenue run rate and raised a $30M seed round led by Khosla Ventures.

Our founders previously grew Mercor's code team from $0 to $500M in annualized revenue run rate, leading its largest code engagements and synthetics work. Our team brings experience from Google DeepMind, Etched, Nvidia, Stanford SAIL, and Berkeley RISE, including TerminalBench co-authorship.

We're a small team of engineers and researchers working in-person in FiDi, 5 days a week.

What you'll do

• Create new frontier training environments and task formats from production agent traces.

• Analyze agent failures and run experiments to measure training value, working directly with frontier researchers on new benchmarks and task formats.

• Build core infrastructure for automated creation, quality control, and evaluation of training environments at scale.

What we're looking for

• Published agent benchmarks or experience scaling synthetic data or post-training pipelines.

• Strong engineering ability: you can turn a research idea into a working system and produce results others can reproduce.

• Good experimental judgment: you can distinguish model failures from problems in the data, environment, or evaluation.

Compensation & Benefits

• Extremely aggressive quarterly performance bonus structure with 7-figure upside

• Generous equity grant vested over 4 years

• $10K housing bonus (if you live within 0.5 miles of our office)

• Free Equinox membership

• Free lunch & dinner

• Health, Dental, Vision insurance

Apply

Apply through this page with your resume and links to benchmark work, published papers, codebases, or other evidence of exceptional talent. Tell us what you personally contributed.

We also offer a $50,000 referral bonus.