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Computer Vision & Embedded Systems Engineer

MycoSense Inc.
Cully, VD

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Détails de l'emploi

Qualifications

Niveau Doctorat
Niveau Master
Équipement informatique
Python

Description complète du poste

APPLY

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: Retrain standard industry models and optimize them for use in edge devices.

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 Python, numpy and opencv bindings, optimizing code for fast execution
The Hardware: Deep hands-on experience with the NVIDIA Jetson ecosystem (Orin/Xavier)

Deployment: Proven track record of deploying algorithms 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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