Hiring: Staff Product Manager - Data Products Company: Snorkel AI Location: San Francisco, CA Job Posted Time: 2026-09-15 07:37:32 Target Skills & Keywords : Data Pipeline, LLM, Python About the job Experience: •4-6 years of experience shaping technical roadmaps and working with researchers as stakeholders •6 years of experience shaping technical roadmaps and working with researchers as stakeholders Required Skills: •This role is highly cross-functional, sitting between Research, GTM and Operations. As a founding member for this role, you will be in charge of setting up the frameworks to build the roadmap, gather data from relevant sources, and share the roadmap with both internal and external stakeholders. •Own the "data as a product" roadmap for Snorkel's Agentic and RL Environment focus areas, working x-functionally with research, academic partners, and GTM to define the skills and capabilities for our datasets •Shape new "data" product areas and work with academic partners and research leaders to build Snorkel's competitive edge in the market •Collaborate cross-functionally to help shape the roadmap and data strategy and influence business strategy Qualifications: •Comfort with ambiguity and working with multiple technical and non-technical stakeholders •AI and ML fluency, especially related to Frontier Agentic Workflows and RL Environments •8+ years in product management, including 3+ years at senior/staff level owning a roadmap end-to-end (or 6+ years with a PhD/research background in ML) •Demonstrated ownership of a technical product where data itself was the deliverable — datasets, benchmarks, evals, annotation pipelines, or labeled corpora sold or shipped to external consumers •Working fluency in modern LLM post-training: SFT, preference data (RLHF/RLAIF), RLVR, reward modeling, and how data composition affects model capability. Must be able to hold a substantive conversation with a research scientist without an interpreter •Operational familiarity with agentic systems and the current agentic eval landscape (e.g. SWE-bench-style coding evals, terminal/computer-use benchmarks, tool-use and long-horizon task evaluation) and an informed view on where they fall short •Track record building product frameworks from zero — prioritization models, roadmap artifacts, intake processes — in an environment with no existing playbook •Direct customer-facing experience with highly technical buyers; ability to run a discovery conversation with an ML researcher or post-training lead and convert it into a roadmap commitment •Quantitative rigor: can size a market, model unit economics of a data program (cost per trajectory/task/environment), and defend prioritization with numbers •Strong technical foundation — comfortable reading research papers, discussing training dynamics with scientists, and reasoning about data pipelines end-to-end. Compensation: •$260,000 - $300,000 / year Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!