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Join our team developing the hottest apps in the industrial mushroom farming sector. As Senior Computer Vision & Embedded Systems Engineer focused on leading-edge computer vision & robotics applications, you will play a pivotal role in developing and applying cutting-edge technologies to optimize key aspects of our mushroom cultivation processes.
At MycoSense, we aren't just building models; we are building the eyes of industrial mushroom cultivation. You will be responsible for the end-to-end vision pipeline that powers our vision units and robot integrations. We work in the real world—where lighting changes, dust exists, and latency kills.
LOCATION
Cully, Switzerland
EMPLOYMENT TYPE
Permanent
What You’ll Do
- Architect Vision Pipelines: Design and deploy real-time CV systems for mushroom detection, grading, and room scanning that run 24/7 in industrial environments.
- Hardware Ownership: Select and integrate industrial camera sensors, optimize optics, and manage the vision interface with NVIDIA Jetson Orin modules.
Edge Optimization: Take models from PyTorch/TensorFlow and squeeze every millisecond of performance out of them using TensorRT, CUDA, and C++.
Robotics Integration: Work directly with the robotics team to close the loop between vision perception and high-speed robotic picking (Delta-robots).
Physical Debugging: Solve the hard problems of "Vision in the Wild," including motion blur, varying focal planes, and environmental interference.
Who You are
- Experience: 5+ years of professional experience in Computer Vision, specifically for industrial automation, robotics, or medical imaging.
- The Stack: Advanced proficiency in C++ and Python. If you can’t write a performant C++ wrapper for a vision task, this isn't the role for you.
The Hardware: Deep hands-on experience with the NVIDIA Jetson ecosystem (Orin/Xavier) and the DeepStream SDK.
Library Mastery: You know OpenCV inside and out (not just the high-level wrappers).
Deployment: Proven track record of deploying Deep Learning models into production environments where "latency" is a critical KPI.
Education: Master’s or Ph.D. in CS, EE, or Robotics—but your portfolio of shipped physical products matters more than your thesis.
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