Product Operations Lead

San Francisco, CA · On-site · Full-time Compensation: $150,000–$250,000 + competitive equity

About the Company

Our client is an AI research lab focused on video data — building exabyte-scale video infrastructure, novel video-understanding techniques, and datasets that push the frontier of video modeling. It works with frontier AI labs and enterprise customers on highly specific dataset problems, building custom algorithms, models, and data pipelines at scale across video, audio, and multimodal data for AI training and evaluation. Its data has earned the trust of frontier AI labs, Fortune 100 companies, and fast-growing generative-AI startups. The team is roughly 25 people, capital-efficient, and shipping directly into the models defining the frontier.

Founded 2022 · ~25 people (Seed) · Industry: AI Tools

The Role

Own the day-to-day execution and scaling of the client'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. Best fit is someone early in their career with strong technical instincts, high communication skills, and a bias to build.

What you'll be doing

• Operate and scale the internal data-ops platform, including workforce management and QA workflows
• Drive platform and partnership growth through acquisition campaigns and sourcing channels
• Source, onboard, and manage a distributed human workforce for data annotation and curation
• Build and improve QA processes to frontier-AI-lab standards
• Own product ops for the data platform and work with engineering on tooling improvements
• 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

• A mixed technical and non-technical skillset, comfortable with data tooling and light scripting
• Strong organizational skills and attention to detail across multiple concurrent work streams
• 1–5 years of experience, startup environment preferred
• On-site in San Francisco, full-time

Nice to Haves

• Experience managing human-in-the-loop data operations or annotation pipelines
• At least a year of engineering experience or strong technical fluency
• Early-hire experience at a startup, or ops leadership at an AI lab
• Familiarity with data-quality frameworks or ML data pipelines
• A data-space background

Why Join

• Ship into frontier models: your operational work directly powers the datasets frontier AI labs, Fortune 100s, and top generative-AI startups train on
• True 0→1 ownership: build workforce, QA, and growth workflows from scratch with no playbook
• A high-leverage seat on a small (~25-person), capital-efficient team reporting into the founding team
• Strong comp and perks: $150K–$250K + competitive equity, 401k, full health insurance, all meals covered, and rides home

Details

• Location — San Francisco, CA
• Work policy — On-site
• Compensation — $150,000–$250,000 + competitive equity
• Visa sponsorship — Available (H-1B, OPT)
• Employment type — Full-time