About HUD

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.

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 and model-assisted), and feedback loops

• Continuously integrate QC 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

• 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 don't meet all criteria.

Team & company details

• Team Size: ~25 people currently, mostly full-time in-person, but some remote.

• Our team: Our team includes 4 International Olympiad medalists (IOI, ILO, IPhO), the former #1 ranked Catan player in the world, serial AI startup founders, and researchers with publications at ICLR, NeurIPS, etc.

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

Logistics

• Employment: Full-time.

• Location: We have offices in San Francisco or Singapore but are open to remote candidates who can work hours that 70-80% overlap with either San Francisco or Singapore time zones.

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

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

What we offer

• Competitive compensation

• 100% covered top-of-the-line medical, dental, and vision (US and Singapore employees)

• Lunch and dinner for in-office employees

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

• 401k with a 4% match

• Other perks including an Equinox membership and commuter benefits (US employees) and a health/wellness stipend (Singapore employees)

• 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.

• Two top-floor offices in San Francisco’s Union Square and Singapore’s Raffles Place

• Annual travel budget to visit either office

Compensation

Actual offers are adjusted for experience and location, but our base salary bands are

• San Francisco (and other major US cities): $135,000 - $230,000

• Singapore: $100,000 - $175,000

• Rest of world: $100,000 - $175,000

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!