Research Engineer, QC Automation

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. Weve raised $16M from top VCs and were YC W25.

Were looking for Research Engineers to automate QC for training data created by companies using HUDs infrastructure. Youll build the systems that scale quality to help us meet our continued strong demand.

• 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 and model-assisted) and feedback loops

• Continuously integrate QC learnings into infrastructure tools and data vendor portal to reduce anomalies inconsistencies and edge cases

You may be a good fit if you have:

• Proficiency in Python Docker and Linux environments

• Strong understanding of what good data means and how to measure it

• Genuine curiosity of different domains and great at asking questions to understand them

• Built scalable data validation pipelines and automated QA/QC systems end-to-end without a fully prescribed roadmap

• Experience working on benchmarks and evals - you can reason about what makes a task realistic a rubric reliable an environment usable and a trajectory useful for RL training

• Early-stage startup experience with ability to work independently in fast-paced environments

Strong candidates may also:

• Have knowledge of statistics

• Have strong written and verbal communication skills for collaboration with our partners and team members across time zones

• Be comfortable designing metrics experiments and QA/QC processes not just executing them

• Have experience with existing benchmarks and can reason about how to construct tasks in new evals

• Thrive in unstructured problem spaces

We prioritize technical aptitude and learning potential over years of experience. Motivated candidates are encouraged to apply even if they dont meet all criteria.

• Team Size: 15 people currently mostly full-time in-person but some remote.

• Our team: Our team includes 4 International Olympiad medalists (IOI ILO IPhO) serial AI startup founders and researchers with publications at ICLR NeurIPS etc.

• Company stage: We have 8 figures in funding and high revenue growth. Were scaling profitably and quickly to meet very strong demand.

• Employment: Full-time.

• Location: On-site in the San Francisco Bay Area.

• Visa Sponsorship: We provide support for relocation and visas for strong full-time candidates to the US.

• Timeline: Applications are rolling. The process is 2 technical interviews and a 2-3 day work trial.

• Competitive compensation based on experience and location

• 100% covered top-of-the-line medical dental and vision from Blue Shield of CA

• Lunch and dinner when youre in the office

• Company-wide holiday break (Christmas Eve to New Years Day) on top of PTO and paid holidays

• Other perks including an Equinox membership 401k and commuter benefits

• Unlimited* access to tokens for ChatGPT Claude Code Cursor etc. *By unlimited we mean no one on our token usage leaderboard has ever hit a limit. So we have no idea what the limit is.

Due to high volume we may not actively respond to every application but feel free to contact us at or elsewhere if we missed your application!

Required Experience:

IC