AI Engineer – Model Training & Deployment
About the Role
This is an entry-level AI Engineer position on a small ML and robotics team, focused on developing, training, and deploying deep learning models that enable intelligent robotic work cells to perceive and act in real industrial environments. You'll 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 industrial 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 reliably in on-site customer deployments.
Design and run reproducible experiments and evaluations to drive continuous improvement.
What We're Looking For
1+ years of hands-on experience training deep learning models in academic, thesis, or industry projects - with documented results and evaluation metrics.
Proficiency in Python and PyTorch for model development.
Experience with Docker for deployment and environment replication.
Comfortable working in a Linux/command-line environment.
Experience deploying trained models to production or customer environments.
Familiarity with Slurm or other cluster job scheduling systems.
Experience with ONNX or other model export/interoperability tools, with interest in edge/on-device deployment.
Familiarity with data versioning tools such as DVC.
Background or strong interest in computer vision, robotics, or physical systems.
Strong analytical mindset and rigorous approach to experimentation.
Fluency in English; German is a plus.
Location
This is a fully on-site role based in Munich, Bavaria, Germany. Visa sponsorship is not available.