Product Operations Lead

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.

• 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

• 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

• 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