Product Operations Lead

Product Operations Lead San Francisco, CA · On-site · Full-time Compensation: $150,000–$250,000 + equity About the Company An AI data‑infrastructure company building custom algorithms, models, and data pipelines at scale across video, audio, and multimodal data for AI training and evaluation. The team works on highly specific dataset problems for frontier AI labs and enterprise customers, and its work ships directly into the models defining the frontier. Small, capital‑efficient team moving fast. Founded 2022 · ~25 people (Seed) · Industry: AI Tools / AI data infrastructure The Role Own the day‑to‑day execution and scaling of the company's data‑operations platform — the human workforce, vendor partnerships, and QA processes that power it. A scrappy, hands‑on role at the intersection of operational execution and platform growth: run acquisition campaigns to expand the user base, build and improve workflows from scratch, and work directly with engineering to ship tooling improvements. Best fit is someone early in their career with strong technical instincts, high communication skills, and startup experience who can move fast without a playbook. What you’ll be doing Operate and scale the internal data‑ops platform, including workforce management, task assignment, and QA workflows Drive platform growth by running acquisition campaigns, testing new sourcing channels, and expanding the user base Source, onboard, and manage a distributed human workforce for data annotation, curation, and quality review Build and improve QA processes to meet frontier AI lab standards Own product ops for the data platform — work with engineering to ship tooling improvements, track metrics, and identify gaps Create documentation, SOPs, and training materials for operational workflows Tech stack Data tooling, light scripting, and spreadsheet‑level analysis; familiarity with ML data pipelines a plus. Requirements Operate and scale internal data ops platform including workforce management and QA workflows Drive platform and partnerships growth through acquisition campaigns and sourcing channels Source, onboard, and manage distributed human workforce for data annotation and curation Build and improve QA processes for frontier AI lab standards Own product ops for data platform and work with engineering on tooling improvements Create documentation, SOPs, and training materials for operational workflows Mixed technical and non‑technical skillset with comfort in data tooling and light scripting Strong organizational skills and attention to detail managing multiple concurrent work streams 1 to 5 years experience, startup environment preferred SF in‑person, full‑time Green Flags Experience managing human‑in‑the‑loop data operations or annotation pipelines At least 1 year of engineering experience or strong technical fluency Early hire experience at startup or ops leadership at AI lab Familiarity with data quality frameworks or ML data pipelines Data space background a strong plus Red Flags No technical grounding whatsoever Strategy‑only profile with no hands‑on execution No startup exposure Why Join Ship into frontier models — your operational work directly powers datasets for frontier AI labs and top generative‑AI companies train on True 0→1 ownership — build workforce, QA, and growth workflows from scratch with real end‑to‑end ownership High‑leverage seat on a small, capital‑efficient team reporting into the founding team Strong comp and perks: competitive equity, 401k, full health insurance, all meals covered, Ubers home Details Location — San Francisco, CA Work policy — On‑site (in‑person at HQ) Compensation — $150,000–$250,000 + equity Visa sponsorship — H‑1B, OPT Employment type — Full‑time #J-18808-Ljbffr