Job Details

Sieve is the only AI research lab exclusively focused on video data. Video makes up 80% of internet traffic and powers creativity, communication, gaming, AR/VR, and robotics. We believe modeling video will unlock future growth across applications; high-quality training data is the current bottleneck, and Sieve addresses this need.

We combine exabyte-scale video infrastructure, novel video understanding techniques, and multiple data sources to develop datasets that push the frontier of video modeling. Our approach enables datasets with precision, quality, speed, and cost that have earned the trust of frontier AI labs, Fortune 100 companies, and fast-growing gen AI startups.

We are a Series A company backed by Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.

As a software engineer at Sieve, you'll work across the stack to build and scale the data pipelines that create the datasets we deliver to customers. You'll own projects end-to-end: sourcing and curating data, developing ML filters, improving system efficiency, and building internal dashboards for QA and delivery. You'll play a critical role in ensuring customers receive high-quality data on time, every time.

This role is ideal for someone who thrives on solving hard problems, enjoys working directly with customers pushing the frontier of Video AI, and wants to be challenged to achieve at the highest level.

• Build and maintain data pipelines that produce customer datasets.
• Source, curate, and validate data for training and evaluation.
• Develop machine learning filters and tooling to improve data quality and efficiency.
• Improve system performance, reliability, and scalability.
• Develop internal dashboards for QA and delivery workflows.
• Collaborate with customers and external teams to understand requirements and deliver results.

• Strong Python developer; Go or TypeScript experience welcomed.
• Excellent communication skills, especially with customers and external teams.
• Motivated by hard problems and willing to work in a demanding schedule (9-9-6).
• Writes clean, maintainable code.
• Ability to context switch and adapt to changing priorities.
• Bonus: Early startup experience as an initial hire.
• Bonus: Active GitHub or portfolio projects.
• In-person presence at our San Francisco HQ is preferred.

San Francisco, CA

Salary range listed in job postings: typical ranges vary; visit the listing for current figures.