Research Engineer, QC Automation
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
We're looking for Research Engineers to automate QC for training data created by companies using HUD’s infrastructure. You’ll build the systems that scale quality to help us meet our continued strong demand.
Responsibilities
Create QC systems based on true understanding and human judgement, without relying heavily on LLMs
Define and enforce quality standards for training data
Design experiments and metrics to grade agent outputs
Partner with data vendors to debug quality issues and diagnose agent failure modes, provide actionable feedback, and improve their data generation processes
Translate QC learnings into systems for auditing supplier-generated datasets, including sampling strategies, validation pipelines (rule-based
