Deep Learning Engineer
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).
Responsibilities
- Create new neural network architectures and integrate them into 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.
Minimum Requirements
- Bachelors in Computer Science (AI/ML specialization), Statistics, Mathematics (Probability), or equivalent.
- Strong foundations in probability, linear algebra, and optimization.
- Background in machine learning.
Preferred Qualifications
- Experience with large-scale industrial applications of statistical modeling and inference.
- Experience with machine learning in computer vision.
- PhD in Computer Science (AI/ML specialization), Statistics, Mathematics (Probability), or equivalent.