[Hiring] AI Machine Learning Engineer 3D Developer @Imnoo AG

Role Description

Geometry with consequences. Deep learning on 3D CAD data where correctness translates into steel and aluminum, not pixels. The ultimate tinkerer's playground. Physical machines, shop floors, and modern cloud architectures all in one stack. Tangible impact. Your work feeds the data pipelines that power our AI quoting and calculation engines. Factories operate differently because of what you ship. High autonomy. A fragmented industry full of unsolved problems, and the freedom to prototype, test, and deploy your own solutions end-to-end.

What you'll do:

• Develop advanced feature-extraction and data-processing solutions for 3D CAD, 2D, and batch data feeding our machine learning systems.
• Build, train, and industrialize deep learning models that understand geometry and drive our quoting, calculation, and optimization engines.
• Enhance and extend our 2D/3D/CAD tools and geometry solutions.
• Design, engineer, and own cloud services, APIs, and automated model training/deployment — from proof of concept to production under real load.
• Go deep across interconnected cloud, data, computer vision, and ML services spanning multiple languages and platforms.

Qualifications

• Machine learning / deep learning experience.
• Real development experience or serious projects: building, training, and shipping models (PyTorch, PyTorch Lightning, scikit-learn or similar), not just coursework or library calls.
• Strong mathematical understanding: Linear algebra, geometry, statistics, probability.
• Strong software engineering: 5+ years across dynamically and statically typed languages (e.g. Python plus C++/C#), with sharp problem-solving skills.
• Game development / 3D foundations: Hands-on experience in game development, 3D geometry, rendering, fluid simulations, CUDA/GPU programming, or similar.
• Production experience: You've built or maintained systems running under heavy load.

Requirements

• Nice to have: CAD system development experience; CNC / mechanical industry exposure.
• ML industrialization: ONNX, quantization, Docker, MLOps practices, automated model training and deployment.
• Large-dataset work: processing, clustering, filtering, indexing, and querying; statistical testing and outlier analysis.
• Cloud services (AWS/Azure), SQL and NoSQL databases, full-stack experience (e.g. Angular).

Benefits

Imnoo is sustainability focused, creating real value as well as a profitable company with a stable base. We aren't just riding the recent AI wave; we have been deeply rooted in machine learning and statistical analysis for 10 years, delivering real, measurable value to a stable, loyal client base of manufacturers.