Computer Vision Engineer

Zivid is a Norwegian scale-up leading the way in 3D sensor technology for both established and next generation robotics applications. We’re looking for a skilled and versatile Computer Vision Engineer to join our cross-functional Vision team working at the frontier of 3D vision. This position is open both to junior engineers and highly experienced senior and principal applicants.

Job Description

As a Computer Vision Engineer at Zivid, you’ll work at the intersection of research and product development – directly shaping the core of our 3D vision platform. Your contributions will span from algorithm prototyping and design in Python to implementing production-ready, high-performance features into our C++-based end-user software product.

More Concretely, You Will

• Design and implement core algorithms for 3D reconstruction and point cloud processing
• Optimize our compute pipeline, including pattern decoding, filtering, and machine learning components
• Ensure the quality of our 2D color and 3D data outputs, improving accuracy, speed, and robustness
• Develop machine learning models and efficiently integrate them into the end-user software
• Develop tools for robot and vision systems calibration
• Work in Python, C++ and GPU frameworks (like CUDA or OpenCL) to improve our compute pipeline
• Take ownership of features end-to-end - from research and prototyping to design, implementation, testing and deployment
• Collaborate with hardware, firmware, and software engineers across R&D and customer-facing projects
• Solve practical customer challenges by converting creative ideas into usable solutions
  
  

Zivid industrial 3D sensors are the best in the business, powering a broad range of robotics and automation systems worldwide. We’re small enough to move quickly and act on new opportunities, yet established enough to have deep insight into customer needs and real problems worth solving. Together, we will innovate in 3D machine vision and create new solutions to previously unsolved problems in machine vision.

WE ARE LOOKING FOR

• MSc or PhD in Computer Vision, Computer Science, Physics, Signal Processing, or a related field
• Experience with computer vision and image processing
• Solid foundation in mathematics, in particular linear algebra
• Solid experience in Python and/or C++
• Strong communication skills and a structured, solution-oriented mindset
• Motivation to write clean, tested, and maintainable code
  
  

Bonus Qualifications

If you have any of these, it’s a strong plus:

• Experience with GPU programming, e.g. OpenCL, CUDA or Halide
• Background in real-time processing or performance optimization
• Experience with machine learning frameworks (e.g., PyTorch, TensorFlow) for training and inference
• Familiarity with vision system calibration and signal processing
• Experience with 3D vision libraries such as OpenCV, Open3D, or Point Cloud Library
• Familiarity with agile development, CI pipelines and automated testing
  
  

WE OFFER

• Competitive compensation package, including sign-on stock options package, competitive pension scheme, and premium health insurance plan
• Focus on code quality and learning: Tech talks, pet-project hackathons, code reviews, design reviews, and peer programming
• A software team dedicated to quality, testing, clean code, and a modern toolchain
• A large degree of autonomy and big opportunities for career advancement
• An open, creative, collaborative, and innovative environment in a young company with a competent, agile, and international team
• Social events like climbing, running, cage ball, movie night, and company cabin trips
• The opportunity to work with exciting hardware and software technologies defining the future of 3D vision
  
  

Location: Nydalen, Oslo, Norway. On-site.

Start date: As soon as possible (upon agreement).

Application deadline: We review applications continuously, but no later than September 1st.

If you have specific questions about the position, reach out to Espen Holmbakken, Principal Engineering Manager: [email protected] .