Technical Program Manager

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 $16M from top VCs and were YC W25.

We’re looking for a Technical Program Manager to own complex, time-sensitive data and evaluation programs for frontier AI labs, data vendors, and internal teams. You’ll turn ambiguous technical asks into executable programs, coordinate the people and dependencies required to deliver them, and ensure the resulting data is genuinely useful for evaluating and improving LLMs and agents. You’ll also manage vendors and build the processes, tooling, and operating rhythms that allow HUD to deliver reliably at increasing scale.

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  Own data and evaluation programs end-to-end, from initial scoping and requirements gathering through production, quality assurance, delivery, and retrospective

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  Translate ambiguous requests from AI labs and internal teams into clear specifications such as milestones, owners, dependencies, acceptance criteria, etc.

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  Maintain and improve data quality procedures using both quantitative signals and qualitative inspection, including analyzing task coverage, difficulty, reward distributions, etc.

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  Maintain and improve delivery pipelines at scale, which includes managing external vendors throughout the delivery lifecycle

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  Streamline the logistics behind data production and evaluation programs by improving workflows, documentation, automation, and cross-functional handoffs

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  Partner with research, platform, marketplace teams to translate learnings and feedback into product improvements

• Experience owning complex technical programs in AI/ML, data operations, support engineering, applied research, forward-deployed engineering, or a similarly cross-functional environment

• Strong quantitative and qualitative judgment about data—you can move between aggregate metrics and individual examples to determine whether a dataset or evaluation is useful, reliable, and representative

• Experience maintaining and improving complex processes, especially within project delivery or data contexts

• Demonstrated ability to bring structure to ambiguous problems, maintain momentum as requirements change, and make sound tradeoffs without waiting for a perfect specification

• Strong written and verbal communication skills, including the ability to turn messy technical information into clear decisions, owners, and next steps

• Experience with RLHF, reinforcement-learning environments, agent evaluations, human-in-the-loop data pipelines, annotation, or expert data collection

• Experience supporting frontier AI labs, technical enterprise customers, or research teams with urgent and evolving requirements

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

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.