Machine Learning Engineer

develop; München; Vor Ort; EUR 70.000 - 120.000; Vollzeit

Benefits dieser Stelle

Equity

Zusammenfassung

develop, a stealth-mode deep-tech startup in Munich, is seeking a Machine Learning Engineer focused on 3D geometry and generative modeling to bridge AI and physical manufacturing.

You will research, build, and deploy ML models for 3D shape understanding, architect data pipelines for geometric data, and own end-to-end production deployment while collaborating with cross-functional teams.

Equity ownership is meaningful, and you will help shape the technical direction and core IP.

Qualifikationen

• 2+ years of ML experience in production.
• Strong Python proficiency and frameworks PyTorch or TensorFlow.
• Hands-on with 3D spatial data.
• Background in computational geometry, CAD/CAM libraries, or specialized MLOps infrastructure.

Aufgaben

• Research, build, and optimize ML models for 3D shape understanding, manipulation, and generation.
• Architect robust data pipelines for geometric formats into ML-ready representations.
• Implement efficient training workflows for geometric deep learning and large-scale spatial models.
• Own the end-to-end deployment of models into production, optimizing for speed and scale.
• Collaborate with cross-functional teams to integrate generative capabilities into the core platform.

Kenntnisse

Python

PyTorch

TensorFlow

3D spatial data

Computational geometry

CAD/CAM libraries

MLOps

Tools

CAD/CAM libraries

MLOps infrastructure

Jobbeschreibung

We are representing a stealth-mode, venture-backed deep tech start-up based in Munich that is reimagining how physical components and hardware are designed. They are looking for a Machine Learning Engineer with a specialized focus on 3D geometry and generative modeling to build core systems that bridge the gap between AI and physical manufacturing.

What You'll Do

• Research, build, and optimize advanced machine learning models for 3D shape understanding, manipulation, and generation.
• Architect robust data pipelines capable of processing complex geometric formats into ML-ready representations.
• Implement efficient training workflows for geometric deep learning and large-scale spatial models.
• Own the end-to-end deployment of models into production, optimizing for speed and scale.
• Collaborate closely with cross-functional teams to integrate generative capabilities into the core platform.

What You Need

• 2+ years of ML experience in production
• Strong proficiency in Python alongside core ML frameworks like PyTorch or TensorFlow.
• Hands-on experience working with 3D spatial data
• Background in computational geometry, CAD/CAM software libraries, or specialized MLOps infrastructure.

Why Apply?

• Meaningful equity ownership.
• Shape the technical direction and core IP as an early foundational team member.
• Solve hard, highly technical problems at the intersection of AI, computer vision, and physical engineering.