About the role
About HUD
HUD is building infrastructure to create RL training data and evals for frontier AI agents, as well as a marketplace to sell these to frontier labs through the HUD marketplace. Our platform is used by frontier labs, Fortune 500 companies, and startups. We’ve raised $16M from top VCs and were YC W25.
About the role
This is a general application for candidates who are unsure which research focus - QC Automation, Benchmarks, or Synthetic Data - they would be a fit for. We would love to meet you and figure it out together. However, if you already have a focus in mind, please apply to only that application.
We're looking for Research Engineers to build the technical foundation for training and evaluating frontier AI agents. You’ll build the systems for creating new environments, improve data quality, and translate real-world workflows into tasks and benchmarks.
Responsibilities
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Build systems for creating, running, evaluating, and improving agent training environments
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Design experiments to understand model behavior, agent failure modes, and data quality issues
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Develop tools that help researchers, engineers, and data vendors create higher-quality tasks, trajectories, and feedback loops
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Work across the full lifecycle of agent training data - task design, environment setup, trajectory collection, evaluation, and validation
