Sieve
Product Operations Lead
San Francisco
Sponsorship not specifiedDetected 226 days ago
SwiftMachine LearningData EngineeringAR/VRCommunicationOrganizational Skills
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odds of building a lasting career here
34Risky
Cap-exempt (no lottery)0
Sponsors this role70
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
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Files H-1B transfers
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About the role
- This is a deeply operational and semi-technical role.
- 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.
Responsibilities
- 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
- 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
- able to manage multiple concurrent work streams
Requirements
- Bachelor's degree in CS, STEM, or equivalent practical experience
- Build and improve QA processes to ensure data output meets the standards required by frontier AI labs
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
Company info
- Sieve is a multi-modal lab curating the world's highest-quality training datasets - spanning video, audio, images, text, and 3D. We combine exabyte-scale data infrastructure and novel multimodal understanding techniques 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 partner with top AI labs and did $XXM last quarter alone, as a team of ~30 people. We also raised our Series A from Tier 1 firms such as Matrix Partners https://matrix.vc/, Swift Ventures https://www.swift.vc/, Y Combinator https://www.ycombinator.com/, and AI Grant https://aigrant.com/.
- Sieve is one of the most capital-efficient teams in AI - roughly 30 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.
- Sieve is a multi-modal lab curating the world's highest-quality training datasets - spanning video, audio, images, text, and 3D.
- We combine exabyte-scale data infrastructure and novel multimodal understanding techniques 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 partner with top AI labs and did $XXM last quarter alone, as a team of ~30 people.
- We also raised our Series A from Tier 1 firms such as Matrix Partners https://matrix.vc/, Swift Ventures https://www.swift.vc/, Y Combinator https://www.ycombinator.com/, and AI Grant https://aigrant.com/.
- Sieve is one of the most capital-efficient teams in AI - roughly 30 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.
- Sieve exists to solve the biggest bottleneck in the growth of these applications:
- high-quality training data.
This listing is sourced directly from Sieve's careers page and normalized into a canonical job model.