Computer Vision Engineer (Object Detection & 3D Pose Estimation)

Mujin is a global leader in industrial automation, redefining supply chain efficiency through MujinOS—our intelligent operating system for robotics. At our core is Machine Intelligence (MujinMI), a unique approach that leverages real-time digital twins and advanced perception, planning, and control algorithms to achieve fully autonomous operations.

Our flagship product, MujinController, empowers users with a highly configurable, no-code interface. By integrating cutting-edge motion planning and computer vision, it enables seamless automation for complex applications such as palletizing, picking, and truck unloading.

Headquartered in Japan with a growing presence in the US, China, and Europe, we invite you to join a dynamic environment where you can shape the future of automation.

Minimum Requirements

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)

Preferable Requirements

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 in 3D processing and statistical analysis

Previous contributions to open source projects

Extras: object tracking, SLAM, computer graphics, augmented reality, machine learning, exposure to projects in robotics

Attractiveness

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!

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.

Interview Process:

HR Interview: Discussion with Human Resources.

Hiring Manager Interview (Whiteboard interview): One or two rounds with the hiring manager.