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 $15M from top VCs and were YC W25.

About the role

We're looking for research engineers to help build out QA 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

• Define and enforce quality standards for training data

• Build tooling and workflows to audit supplier-generated datasets, including sampling strategies, validation pipelines (rule-based and model-assisted), and feedback loops

• Determine if and how human-in-the-loop review workflows can be used to optimize QA

• Partner with data vendors to debug quality issues, provide actionable feedback, and improve their data generation processes

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

Experience

You may be a good fit if you have:

• Proficiency in Python, Docker, and Linux environments

• Worked with large-scale datasets

• Evidence of rapid learning and adaptability in technical environments (e.g., programming competitions)

• Startup experience in early-stage technology companies with ability to work independently in fast-paced environments

• Familiarity with current AI tools and LLM capabilities

• Strong communication skills for remote collaboration across time zones

Strong candidates may also:

• Understand of common failure modes in training data

• Have experience building data validation pipelines and/or human-in-the-loop review systems

• Be detail-oriented and able to spot subtle inconsistencies or edge cases in data

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

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.

Team & company details

• 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. We’re scaling profitably and quickly to meet very strong demand.

Logistics

• 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 1-week work trial.

What we offer

• Competitive compensation

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

• Lunch and dinner when you’re in the office

• Company-wide holiday break (Christmas Eve to New Year’s 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 [email protected] or elsewhere if we missed your application!