About the RoleAs a
Research Engineer, you will work across agent training environments, benchmarks, and synthetic data pipelines - shaping how AI agents learn, improve, and are evaluated at scale.
This is an on-site role based in
San Francisco, CA (with a presence also in Singapore). Visa sponsorship is available.
What You'll Do- Build systems for creating new environments, improving data quality, and translating real-world workflows into tasks and benchmarks.
- Design, run, evaluate, and iteratively improve agent training environments.
- Design experiments to understand model behavior, agent failure modes, and data quality issues.
- Develop internal tools that help researchers, engineers, and data vendors produce higher-quality tasks, trajectories, and feedback loops.
- Work across the full lifecycle of agent training data - from task design and environment setup through trajectory collection, evaluation, and validation.
- Partner with external vendors to identify bottlenecks and improve the quality and throughput of the data pipeline.
- Build metrics and analyses to assess whether tasks, environments, and evaluations are genuinely useful for training frontier agents.
What We're Looking ForRequired:- 2-4 years of professional experience as a Research Engineer or in a comparable role delivering systems for AI agent training and evaluation.
- Strong proficiency in Python, Docker, and Linux environments.
- Hands-on experience with benchmarks and evaluations for RL training, including reasoning about task realism, rubric reliability, environment usability, and trajectory quality.
- Experience building systems for creating, running, and evaluating AI agent training environments.
- Experience designing experiments and building metrics/analyses to diagnose model behavior, agent failure modes, and data quality.
- Proven ability to build infrastructure, tools, or pipelines in early-stage environments without fully prescribed roadmaps.
Nice to Have:- Experience building internal research infrastructure or data pipelines.
- Experience designing metrics and validation workflows.
- Background in competitive programming, Olympiad mathematics/computing, academic research, or exceptionally strong independent project work.
- Comfort working and communicating clearly across time zones.
Compensation & Benefits- Salary: $150,000 - $250,000 USD annually, depending on experience.
- Equity participation in a well-funded, early-stage company (Series A/B stage).
- Visa sponsorship available.
- Opportunity to work alongside a world-class team at the frontier of AI agent research and infrastructure.
Location- Primary: San Francisco, CA, United States - on-site.
- Singapore office also available for candidates based in Southeast Asia.
- This is not a remote role.
