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Sieve

Applied Research Engineering Intern

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In-Office
San Francisco, CA, USA
In-Office
San Francisco, CA, USA

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About Us

Sieve is the only AI research lab exclusively focused on video data. We combine exabyte-scale video infrastructure, novel video understanding techniques, and dozens of data sources to develop datasets that push the frontier of video modeling. Video makes up 80% of internet traffic and has become the enabling digital medium powering creativity, communication, gaming, AR/VR, and robotics. Sieve exists to solve the biggest bottleneck in growth of these applications: high-quality training data.

We've partnered with top AI labs and did $XXM last quarter alone, as a team of just 15 people. We also raised our Series A last year from Tier 1 firms such as Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.

About the Role

As an applied research engineering intern at Sieve, you’ll help build high performance building blocks and large scale pipelines to understand video with high precision at internet scale. Often this involves working on ambiguous research problems and finding clever techniques to solve them. You will be working in the computer vision, audio processing, and text processing domains.

You’re likely a good fit if you’re comfortable working with models + APIs and squeezing every drop of performance out of them through clever pre/post-processing, parallelism, pipelining, inference optimization, and occasionally fine-tuning.

Requirements
  • Excellent communication skills

  • Deep passion for the video domain and media technologies

  • Motivated by building end-to-end products—not just training models

  • Able to break problems down from customer level impact to necessary building blocks.

  • Bonus: Active contributor to open source projects

  • In-person at our SF HQ

Benefits
  • Breakfast, Lunch, and Dinner covered and your choice of snacks

  • Ubers covered home

  • Team outings & off-sites!

HQ

Sieve San Francisco, California, USA Office

San Francisco, CA, United States

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