Machine Learning / Computer Graphics Engineer (remote part/full time) - Junior/Mid/Senior
Imnoo AG Open At a glance
Junior Machine Learning Engineering role at Imnoo AG. Remote, Switzerland · full-time.
Pay not stated Machine Learning Engineering salary
remoteroles summary, based on the employer's posting.
What you'll do
- Build feature extraction and data-processing pipelines for 3D CAD, 2D and batch inputs used by machine learning systems
- Train and prepare deep learning models to interpret geometry for quoting, calculation and optimization
- Improve the 2D, 3D and CAD tools used in the role’s geometry workflows
- Take cloud services, APIs and automated model training and deployment from prototypes into production
- Work across connected cloud, data, computer vision and machine learning services written for multiple platforms
What you bring
- You have built, trained and shipped machine learning models through real development work or substantial projects
- You bring strong grounding in linear algebra, geometry, statistics and probability
- You have at least three years building software in dynamically and statically typed languages
- You have hands-on 3D foundations, such as game development, geometry, rendering, simulations or GPU programming
- You have built or maintained systems that operate under heavy workloads
Who this fits
This role suits an engineer who wants to combine machine learning, 3D geometry and production software, with work spanning cloud systems and factory-floor hardware. The posting describes the opportunity as remote and lists Berlin, Germany as the location.
From the employer
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.
For over 10 years at Imnoo at Imnoo, we are bridging the gap between applied artificial intelligence and heavy industrial machinery.
Imnoo is sustainability focused, creating real value as well as a profitable company with 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.
Imnoo is a leading SaaS platform built to analyze CNC parts, automate quoting and planning, and seamlessly connect the cloud with real manufacturers and shop-floor machines. We are looking for a unique hybrid (a CAD AI IoT Engineer / Tinkerer) who thrives at the intersection of software architecture and physical hardware. You won't just be writing code behind a desk; you will be the mastermind connecting our battle-tested algorithms directly to the pulse of the factory floor. If you love reverse-engineering industrial protocols, building edge data pipelines, and parsing complex 3D geometry to automate the business of manufacturing, this is your playground.
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. Our problems are mathematical at their core; this is a real requirement, not a nice-to-have.
Strong software engineering. 3+ years across dynamically and statically typed languages (e.g. Python plus C++/C#), with sharp problem-solving skills.
Computer Graphics / Game development / 3D foundations. Hands-on experience in game development, 3D geometry, rendering, fluid simulations, CUDA/GPU programming, or similar. This is a headline requirement, not a bonus.
Production experience. You've built or maintained systems running under heavy load.
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).
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