ML Engineer - 3D Geometry for CAD (m/w/d)

Worldwide | Sept. 22, 2026

Report as Closed

Company: Kyrall

Country: Worldwide

Type: Onsite

Employment: Full Time

Description:

We're building the world's fastest way to design real, functional 3D parts. Kyrall's AI-powered design agent turns ideas into ready-to-manufacture 3D models in seconds.
Backed by top European VCs, we're a young, well-funded startup based in Munich and we're just getting started.

The Role

As a Machine learning Engineer specialized in 3D geometry, you'll develop models that understand, manipulate, and generate CAD parts. You'll work on challenging problems involving 3D representations, geometric relationships and manufacturability.

What To Expect

• Build and optimize ML models for 3D shape understanding and generation

• Design data pipelines that process CAD formats into ML-compatible representations

• Implement efficient training workflows for geometric deep learning

• Deploy models to production and optimize for performance

• Collaborate with product and engineering to integrate ML capabilities

Your Profile

• 2+ Years of working ML experience

• Strong knowledge of PyTorch or TensorFlow

• Experience with 3D data representation (B-Reps, point clouds, meshes, voxels, implicit surfaces)

• Proficiency in Python and ML engineering best practices

• Proven track record of bringing ML models to production

Nice To Have

• Experience with CAD/3D software/libraries

• Knowledge of computational geometry algorithms

• Experience with MLOps tools and practices

Why Kyrall?

We're reinventing how machines are designed and built, from the ground up.

Our mission: build the world's first truly functional hardware design agent. 3D modeling tools were the last major leap in this space, but the way we design parts today has hit its limit. It's time for something radically better, and we're at the start of it.

As one of our first hires, you won't just execute the vision, you'll help shape it, with a competitive salary and stock options to match.

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