Product Operations Lead

Sieve
  • San Francisco, California
    30+ days ago

    Job Description

    About Us

    Sieve is an AI research lab building the world's highest-quality multimodal datasets — spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure, novel multimodal understanding techniques, and dozens of proprietary data sources to develop datasets that push the frontier of foundation models. Video alone makes up 80% of internet traffic, and across modalities, data has become the enabling medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in the growth of these applications: high-quality training data.

    We've partnered with the world's top AI labs and did $XXM last quarter alone, as a team of just ~25 people. We also raised our Series A from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.

     

    Why Now

    Sieve is one of the most capital-efficient teams in AI — roughly 25 people serving the world's leading AI labs across every major data modality. You'll join early, own problems end-to-end, and watch your work ship directly into the models defining the frontier.

    About the Role

    As Product Operations Lead, you'll own the day-to-day execution and scaling of Sieve's data operations platform alongside vendor partnerships. 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 and partnerships 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

    Numbers & Facts

    LocationSan Francisco, California
    Websitehttps://www.sievedata.com/

    Skills

    • Accounts Receivableunmatched
    • Analysis Skillsunmatched
    • Artificial Intelligence (AI)unmatched
    • Campaignsunmatched
    • Data Managementunmatched
    • Data Processingunmatched
    • Data Qualityunmatched
    • Data Setsunmatched
    • Detail Orientedunmatched
    • Engineeringunmatched
    • Gamingunmatched
    • Insuranceunmatched
    • Machine Toolunmatched
    • Machining Operationsunmatched
    • Metricsunmatched
    • Modalityunmatched
    • Onboardingunmatched
    • Operational Improvementunmatched
    • Organizational Skillsunmatched
    • Process Improvementunmatched
    • Product Programsunmatched
    • Quality Assuranceunmatched
    • Quality Assurance Methodologyunmatched
    • Research Laboratoryunmatched
    • Roboticsunmatched
    • Scripting (Scripting Languages)unmatched
    • Spreadsheetsunmatched
    • Training Data Setsunmatched
    • Vendor/Supplier Selectionunmatched
    • Website Trafficunmatched
    • Workforce Managementunmatched

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