Research Engineer automating quality control for training data that companies produce on HUD's infrastructure. Builds QC systems, sampling strategies, rule-based and model-assisted validation pipelines, and feedback loops with data vendors. Requires Python, Docker and Linux.
HUD's mission is to build reliable, fair and open infrastructure for AI data. We want data to be valuable for the people who create it and trustworthy for the labs that train on it. Our team is a quickly growing group of researchers, engineers and operators building the economy that shapes what AI will become. Backed by $16M from top VCs and YC (W25), our marketplace and platform are used by startups, Fortune 500 companies and frontier labs.
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.
You may be a good fit if you have:
Strong candidates may also:
We prioritize technical aptitude and learning potential over years of experience. Motivated candidates are encouraged to apply even if they don't meet all criteria.
Actual offers are adjusted for experience and location, but our base salary bands are
Due to high volume, we may not actively respond to every application, but feel free to contact us at [email protected] or elsewhere if we missed your application!
Compensation: $100K - $230K