AI / Machine Learning Engineer
Computer Vision & 3D Inspection
80–100% · Lugano, Switzerland
The role
Lumaspect is an early-stage technology company developing intelligent inspection and automation systems for electronics manufacturing. We combine machine vision, precision hardware and AI to help manufacturers improve quality and automate production.
We are looking for an engineer who enjoys turning experimental methods into working inspection systems. You will work with images and measurements from real hardware, combining classical computer vision and machine learning to detect defects and evaluate product quality.
What you will do
- Develop methods for component recognition, defect detection and dimensional measurement on electronic assemblies.
- Build image acquisition, preprocessing and annotation workflows with the hardware team.
- Evaluate existing models and datasets, adapting them to our applications and developing custom approaches where needed.
- Work on camera calibration, image registration and 3D reconstruction.
- Design reproducible experiments and measure detection performance, false positives, inference time and robustness.
- Integrate models into inspection software and maintain versioned datasets, evaluation results and deployment pipelines.
What you bring
- A qualification in computer science, engineering, applied mathematics or a related field, or equivalent practical experience.
- Practical experience developing and evaluating computer vision or machine learning systems.
- Strong Python skills and familiarity with PyTorch or a comparable framework, OpenCV and numerical computing.
- Understanding of dataset quality, annotation, validation and the risks of overfitting or data leakage.
- Sound software engineering practices, including Git, testing and reproducible experiments.
- Working proficiency in English and Italian preferred; strong candidates still developing one language are welcome.
Experience with industrial inspection, anomaly detection, limited-data learning, structured light, point clouds or edge deployment would be valuable. We welcome candidates who can demonstrate relevant work through deployed systems, research or substantial personal projects.
Apply
Send your CV and a short description of a vision or machine learning project, explaining your contribution and how you evaluated its performance. Links to code, publications or demonstrations are welcome.