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You will own end-to-end data and evaluation programs for AI labs, translating ambiguous technical requirements into structured, executable specifications. Additionally, you will manage external vendors and improve data quality pipelines to support frontier AI development.
This 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 data and evaluation programs for frontier AI labs and internal teams, turning ambiguous technical asks into well-structured, executable programs. Your work directly improves the quality of LLM and agent evaluation at scale.
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 data production logistics by improving workflows, documentation, automation, and cross-functional handoffs.
Partner with research, platform, and marketplace teams to translate learnings and feedback into product improvements.
3+ years owning complex technical programs in AI/ML, data operations, support engineering, applied research, 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.
Experience maintaining and improving complex data quality procedures using both quantitative metrics and qualitative inspection methods.
Experience managing external vendors and scaling delivery pipelines.
Background supporting frontier AI labs, technical enterprise customers, or research teams with urgent and evolving requirements.
Experience with RLHF, reinforcement-learning environments, agent evaluations, human-in-the-loop data pipelines, annotation workflows, or expert data collection.
Strong written and verbal communication skills, with the ability to turn complex technical information into clear decisions and next steps.
Early-stage startup experience and comfort working independently in fast-paced environments.
Competitive compensation package including equity. Full benefits include 100% employer-covered medical, dental, and vision insurance, a 401k, commuter benefits, and unlimited access to leading AI productivity tools. Visa sponsorship and relocation support are available for strong full-time candidates.
On-site in San Francisco, CA or Singapore. Remote candidates who can maintain 70 to 80% time zone overlap with either office location are also welcome to apply.
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