Open Role
About the role
HUD is building reliable, fair and open infrastructure for AI data. Open role focused on operations within HUD’s growing team; location-flexible with timezone overlap requirements and visa sponsorship for strong candidates.
Responsibilities
- Tell us what you’d like to do and how this would help HUD grow. Please be specific and don’t apply unless you’ve done research on HUD and our work. Remember, this is your chance to pitch us on why we should hire you.
- We’re always looking for talent across Research, Engineering, GTM, and Operations.
- If none of the open roles are a fit but you think there’s something you can contribute to HUD, let us know here.
Qualifications
- Experience: 3+ years
- 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.
Skills
Benefits
- 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
- Other perks including an Equinox membership, 401k, and commuter benefits (US employees) and a health/wellness stipend (Singapore employees)
- Unlimited access to tokens for ChatGPT, Claude Code, Cursor, etc.
- Two top-floor offices in San Francisco’s Union Square and Singapore’s Raffles Place
- Annual travel budget to visit either office
About hud
Platform for building RL environments and evals
HUD (YC W25) is developing agentic evals and RL environments for Computer Use Agents (CUAs) that browse the web for frontier AI labs. Our CUA Evals framework is the first comprehensive evaluation tool for CUAs. People don't actually know if AI agents are working reliably. To make AI agents work in the real world, we need detailed evals for a huge range of tasks. We're backed by Y Combinator, and work closely with frontier AI labs to provide agent evaluation and training infrastructure at scale.
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