Sieve is the only AI research lab exclusively focused on video data. Video makes up 80% of internet traffic and has become the enabling digital medium powering creativity, communication, gaming, AR/VR, and robotics. We believe the ability to model video will be the key unlock to the future growth of these applications and as new use cases emerge, high-quality training data becomes the bottleneck. This is where Sieve comes in.
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. This combination allows us to develop datasets at a level of precision, quality, speed, and cost that has gained the trust of frontier AI labs, Fortune 100 companies, and fast-growing gen AI startups.
We've scaled from 0 to $XXM in revenue in the last 3 months with a relatively small team of 11 people, growing 25% month over month. We’re a Series A company and have raised from top-tier firms such as 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 have ownership over projects end-to-end: from how data is sourced and curated, to 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.
Strong Python developer, experience in Go or Typescript also welcome
Excellent communication skills, especially with customers and external teams
Motivated by hard problems that require a 9-9-6 schedule
Writes clean, maintainable code
Able to context switch at a moment's notice
Bonus: Experience as an early hire at a startup
Bonus: Active GitHub or portfolio projects
In-person at our SF HQ
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