AI Engineer - Model Training & Deployment
About the Role
This is an entry-level AI Engineer position on an ML and robotics team, focused on developing, training, and deploying deep learning models that enable robotic work cells to perceive and act in real industrial environments. You will have hands-on impact from day one, with room to grow into deployment and MLOps responsibilities as the stack matures.
What You'll Do
Train and implement deep learning models as part of a core robotics product.
Iterate on model architectures and training pipelines to improve real-world performance.
Support deployment of trained models to customer and edge environments.
Collaborate closely with the ML and robotics team on the core technical roadmap.
Contribute to getting models running in on-site customer and edge settings.
Design and run reproducible experiments to drive measurable improvements.
What We're Looking For
At least 1 year of hands-on experience training deep learning models using Python and PyTorch, whether from academic projects, a thesis, or industry work, with documented results and evaluation metrics.
Proficiency in Python and PyTorch for model development.
Experience with Docker for deployment and environment replication.
Comfort working in a Linux and command-line environment.
Experience deploying trained models to production or customer environments.
Familiarity with Slurm or similar cluster job scheduling systems.
Experience with ONNX or other model export and interoperability tools, plus interest in edge and on-device deployment.
Background or strong interest in computer vision, robotics, or physical systems.
Familiarity with data versioning tools such as DVC.
Strong analytical mindset and a habit of rigorous, reproducible experimentation.
Fluency in English; German language skills are a plus.
Location
This role is fully on-site in Munich, Bavaria, Germany. Visa sponsorship is not available; candidates must already be eligible to work in Germany.