Member of Technical Staff — Frontier Data
Build reinforcement-learning environments, evaluations, datasets, and scalable infrastructure for frontier AI capabilities. The role suits a high-agency generalist engineer with experience in agents, evaluations, or RL workflows and strong communication skills.
About the job
Responsibilities
- Design and build reinforcement-learning environments, evaluations, and datasets targeting high-value gaps in frontier model capabilities.
- Develop internal platforms and supporting infrastructure to run hundreds of thousands of tasks at scale with high throughput, reproducibility, and observability.
- Collaborate directly with researchers and engineers at leading AI labs to scope dataset development against model roadmaps.
- Build grading harnesses, metrics, and automated checks to measure environment and dataset quality.
- Prototype quickly and harden successful approaches into production systems.
- Contribute to open-source projects where useful to the broader community.
Requirements
- Practical experience with agents, evaluations, or reinforcement-learning workflows.
- Strong technical background and written communication skills.
- Ability to work as a generalist engineer on ambiguous, frontier AI problems.
- High autonomy and a bias toward action.
Nice to Have
- Experience with computer vision or multimodal models.
- Prior experience working with an AI lab as a data or evaluation partner.
Compensation and Benefits
- Base compensation: $150,000–$300,000, depending on experience and performance.
- Equity in the company.
- Health insurance coverage for the employee and eligible family members.
- $4,000 annual travel stipend.
- $350/month productivity stipend.
- $350/month AI stipend.
- $500 one-time home office stipend.
- $150/month team lunch stipend.
- Unlimited paid time off, with an annual two-week minimum.
- 12 weeks of parental leave.
Skills
Reinforcement Learning, AI Agents, Model Evaluations, Ml Tooling, Computer Vision, Multimodal Models, Python, Observability
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