About the job
Sieve is a 15-person AI research lab in San Francisco focused on video data. The team builds exabyte-scale video infrastructure and develops new approaches for video understanding, drawing from diverse data sources to create advanced datasets. With video now accounting for most internet traffic, Sieve aims to solve the challenge of delivering high-quality training data for applications in creativity, communication, gaming, AR/VR, and robotics. The company partners with leading AI labs and has achieved strong financial results, backed by Series A funding from Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
Internship overview
The Applied Research Engineering Intern will help build high-performance components and large-scale pipelines to advance video understanding at internet scale. This role involves tackling ambiguous research problems and turning them into practical solutions. Projects often cover computer vision, audio processing, and text processing.
What you will do
- Develop and optimize models and APIs for video, audio, and text data
- Improve performance through pre- and post-processing, parallelism, pipelining, and inference optimization
- Occasionally fine-tune models for specific tasks
- Work through open-ended research challenges with a small, focused team
Who succeeds here
- Comfortable working with machine learning models and APIs
- Skilled at optimizing systems for speed and accuracy
- Enjoys solving ambiguous technical problems across computer vision, audio, and text domains

