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).
Located in historic Palo Alto, right next to Stanford campus. 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.
- Experience with Deep Learning and CNNs
- 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 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.