About the RoleThis role sits at the intersection of technical program management, data operations, and vendor coordination for an early-stage AI/ML infrastructure company. You will own complex, time-sensitive data and evaluation programs for frontier AI labs and internal teams, turning ambiguous technical asks into executable programs that meaningfully improve LLM and agent evaluation. You will also build the processes, tooling, and operating rhythms that allow the company to scale reliably.
What You'll Do- Own data and evaluation programs end-to-end, from initial scoping and requirements gathering through production, quality assurance, delivery, and retrospective.
- Translate ambiguous requests from AI labs and internal teams into clear specifications with defined milestones, owners, dependencies, and acceptance criteria.
- Maintain and improve data quality procedures using quantitative signals and qualitative inspection, including analysis of task coverage, difficulty, and reward distributions.
- Manage external vendors throughout the delivery lifecycle and improve delivery pipelines at scale.
- Streamline the logistics behind data production by improving workflows, documentation, automation, and cross-functional handoffs.
- Partner with research, platform, and marketplace teams to translate learnings and feedback into product improvements.
What We're Looking For- 3 or more years owning complex technical programs in AI/ML, data operations, support engineering, applied research, forward-deployed engineering, or similarly cross-functional environments.
- Demonstrated ability to translate ambiguous technical requirements into executable specifications with clear milestones, owners, dependencies, and acceptance criteria.
- Strong quantitative and qualitative judgment about data, with the ability to move between aggregate metrics and individual examples to assess dataset quality and representativeness.
- Experience managing external vendors throughout a delivery lifecycle and scaling data production pipelines.
- Background supporting frontier AI labs, technical enterprise customers, or research teams with urgent and evolving requirements.
- Experience documenting, automating, and improving workflows and cross-functional handoffs in project delivery or data contexts.
- Familiarity with RLHF, reinforcement-learning environments, agent evaluations, human-in-the-loop data pipelines, annotation workflows, or expert data collection is a strong plus.
- Early-stage startup experience and comfort working independently in a fast-paced environment.
- A credible, verifiable track record at a strong organization or through substantive company-building experience is preferred.
Compensation & BenefitsCompetitive compensation with fully covered medical, dental, and vision insurance. Additional benefits include a 401k, commuter benefits, unlimited access to leading AI tools, and visa sponsorship and relocation support for strong full-time candidates.
LocationOn-site in San Francisco, CA. Candidates based in Singapore are also welcome. Remote candidates who can maintain 70 to 80 percent time zone overlap with San Francisco or Singapore will be considered.
