companySieve logo

Applied Research Engineering Intern

SieveSan FranciscoNew
On-site Full-time

Clicking Apply Now takes you to AutoApply where you can tailor your resume and apply.


Unlock Your Potential

Generate Job-Optimized Resume

One Click And Our AI Optimizes Your Resume to Match The Job Description.

Is Your Resume Optimized For This Role?

Find Out If You're Highlighting The Right Skills And Fix What's Missing

Experience Level

Entry Level

Qualifications

Strong communication skills are essential. A deep passion for video technologies and the media domain. A drive to build comprehensive end-to-end products, not just train models. A capability to deconstruct problems from customer impact to essential building blocks. Bonus: Experience as an active contributor to open-source projects. This position requires in-person attendance at our San Francisco headquarters.

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

About Sieve

At Sieve, we are breaking new ground in AI research focused on video data, leveraging substantial infrastructure and innovative techniques to create unparalleled datasets. Our commitment to solving critical challenges in video modeling positions us at the forefront of this rapidly evolving field.

Similar jobs

Tailoring 0 resumes

We'll move completed jobs to Ready to Apply automatically.