Product Operations Lead

About Us

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 , Swift Ventures , Y Combinator , and AI Grant .

Why Now

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.

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