As a Computer Vision Engineer, you will be a part of the Mujin R&D team, focusing on the algorithmic design, development, and deployment of computer vision applications for high-speed recognition and the world’s first 3D vision system for factory automation and logistics solutions.
- Solve cutting-edge scientific and technical challenges related to recognition and pose estimation of a very wide variety of objects in challenging scenarios
- Analyze and evaluate state-of-the-art algorithms related to detection and pose estimation, from academic and industrial research, and implement and enhance them in a production environment
- Design, develop and evaluate the performance of highly scalable and accurate real-time computer vision applications, in Python and C/C++
- Perform the detailed test, carry out performance analysis on algorithms, and use continuous integration tools to finely enhance the rapidly deployed algorithms
- Graduating/ Graduated Computer science or relevant faculty in BS, MSc or Ph.D.
- BS or MS with computer vision experience or Ph.D. in Computer Vision related topics
- The ability to develop applications and tools in Python and/or C＋＋
- Technical communication skills in English (reading and writing)
- 3D pose estimation of textured and textureless objects in cluttered scenes, with proven experience
- Python and C++ experience
- Experience with a vast set of computer vision libraries
- Mathematical background
- Previous contributions to open source projects
- Extras: object tracking, SLAM, computer graphics, augmented reality, machine learning, exposure to projects in robotics
We are hiring to expand the team! If you would like to apply real-time computer vision algorithms to robotics and join the industrial automation revolution, this role is for you!
Attractiveness / Uniqueness
- Our computer vision algorithms must be robust to run on 24/7 systems for thousands of items per customer, for diverse customers and applications. We must continue to enlarge its capabilities toward more autonomy, scalability, and diversity of applications.
- The current team members have done research in the world’s top-tier universities and labs in robotics, computer vision, and image and signal processing, such as at Carnegie Mellon University and Stanford University. They have also worked in other industries like robotic inspection and automotive.