HUD trains frontier AI agents and we want your vision.
When you design how humans evaluate and train AI agents on our platform you are making decisions about how people will interact with AI.
What should an AI agent be able to do
When we show training results which figures do users care about and how does it affect their training priorities and downstream model behavior
Whats the line between penalising reward hacking and letting a frontier model provide creative solutions we hadnt even thought of
What should our onboarding docs look like for humans versus autonomous AI agents
Most of the day-to-day is standard design engineering: shipping interfaces iterating on feedback making things work well at scale. You will be listening to users and building things for them. But how you do it matters. After thousands of commits your opinions about human-AI interaction will shape what our entire user experience looks like.
At HUD you are designing a system to train strange and powerful AIs. AIs which are still finding their place in the human world.
We find this mission incredibly fascinating. We hope you will too.
Design and build the HUD RL platforms interface for humans to train evaluate and interact with AI agents
Work closely with ML engineers to translate RL/eval concepts into intuitive usable tools
Talk to users. Make users feel joy and wonder.
Ability to engage with and understand the user experience empathize with them and what their goals are
Balance making good product for users today with having strong opinions on what it could look like tomorrow
Understand when to ship a feature fast and when to push against boilerplate AI slop
Curiosity.
Strong candidates may also have:
Startup experience in early-stage technology companies with ability to work independently in fast-paced environments
Strong communication skills for remote collaboration across time zones
Deep familiarity with current AI tools and LLM capabilities
Understanding of LLM evaluation/RL frameworks and methodologies
Evidence of rapid learning and adaptability in technical environments
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 medallists (IOI ILO IPhO) serial AI startup founders and researchers with publications at ICLR NeurIPS etc
Company stage: We have received tens of millions in venture funding plus very strong demand and revenue growth beyond that. We are scaling profitably and fast to meet demand.
Employment: Fulltime.
Location: On-site only for now. You can join the team in the San Francisco Bay Area or Singapore offices.
Visa Sponsorship: We provide support for relocation and visas for strong full-time candidates to USA or Singapore.
Timeline: Applications are rolling. The process should involve 2 technical interviews and a 1-week work trial.
You will have unlimited access* to API credits for leading providers like OpenAI Anthropic Gemini 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