About Matroid

Matroid makes computer vision simple. We’ve built an easy-to-use and intuitive studio for creating and deploying detectors (computer vision models) to search visual media for people, objects, and events - no programming required.

Founded in 2016 by a Stanford professor, Matroid has raised $33.5 million from NEA, Energize Ventures and Intel Capital and has a broad range of customers and partners in manufacturing, industrial IoT, security, and more. We’re leaders in machine learning and big data. We’ve published research, a textbook, have 10 computer vision patents pending, and annually hold a world-class conference - Scaled Machine Learning (ScaledML scaledml.org).

You’ll be working at our new office in downtown Palo Alto, just a five minute walk from the Caltrain station.

Here are some benefits:

  • Tackle intellectually challenging problems
  • Free lunch, snacks, drinks, and caffeine every day
  • Gym membership with yoga and pilates classes next door
  • Health, dental, and vision insurance with 100% paid premiums
  • Free onsite parking for easy commute, also close to Caltrain
  • Budget for whatever hardware you want
  • Competitive salary and equity
  • Flexible hours


  • Establish and expand the rigorous statistical foundations of the Matroid platform.
  • Develop prototypes and execute experiments to help guide engineering efforts.
  • Explore new model families and machine learning algorithms.

Minimum Requirements

  • Masters in Computer Science (AI/ML specialization), Statistics, Mathematics (Probability), or equivalent.
  • Strong foundations in probability, linear algebra, and optimization.
  • Background in statistical modeling and inference.
  • Experience with Deep Learning and CNNs.

Preferred Qualifications

  • Experience with large-scale industrial applications of statistical modeling and inference.
  • Experience with statistical modeling across a diverse range of data sets and domains.
  • PhD in Computer Science (AI/ML specialization), Statistics, Mathematics (Probability), or equivalent.