About Us Sieve is the only AI research lab exclusively focused on video data. We combine exabyte-scale video infrastructure, novel video understanding techniques, and dozens of data sources to develop datasets that push the frontier of video modeling. Video makes up 80% of internet traffic and has become the enabling digital medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in growth of these applications: high-quality training data. We've partnered with top AI labs and did $XXM last quarter alone, as a team of just 15 people. We also raised our Series A last year from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant. About the Role As Data Operations Lead, you'll own the day-to-day execution and scaling of Sieve's data operations platform. This is a deeply operational and semi-technical role. You'll manage our human workforce, build and improve QA processes, handle people sourcing and onboarding, and drive product ops initiatives that make our platform more efficient. A major part of this role is growth: you'll run campaigns and experiments to expand the platform's user base, find new channels for sourcing, and drive adoption. This role is ideal for someone who is both a builder and an optimizer, someone who can get their hands dirty with tooling while also thinking strategically about how to scale a complex operational machine. What You'll Do • Operate and scale Sieve's internal data ops platform, including workforce management, task assignment, and QA workflows • Drive platform growth: run acquisition campaigns, test new sourcing channels, and grow the user base through creative and scalable strategies • Source, onboard, and manage a distributed human workforce for data annotation, curation, and quality review • Build and improve QA processes to ensure data output meets the standards required by frontier AI labs • Own product ops for the data platform. Work with engineering to ship tooling improvements, track operational metrics, and identify gaps • Create documentation, SOPs, and training materials for operational workflows Requirements • Mixed technical and non-technical skillset, comfortable with data tooling, light scripting, and spreadsheet-level analysis • Strong organizational skills and attention to detail; able to manage multiple concurrent work streams • Growth mindset: experience running or contributing to user acquisition, sourcing campaigns, or platform growth efforts • Bachelor's degree in CS, STEM, or equivalent practical experience • In-person at our SF HQ Nice to Have • Experience managing human-in-the-loop data operations or annotation pipelines • At least 1 year of engineering experience or strong technical fluency • Experience as an early hire at a startup or spearheading ops at an AI lab • Familiarity with data quality frameworks or ML data pipelines Benefits • 401k + Full Health Insurance • Breakfast, Lunch, and Dinner covered and your choice of snacks • Ubers covered home