AI Engineer – Model Training & Deployment

About the RoleJoin an early-stage industrial robotics startup at the forefront of intelligent automation. This is an entry-level AI Engineer position embedded within the ML and robotics engineering team in Munich. You'll work hands-on developing, training, and deploying deep learning models that give robotic work cells the perception and decision-making capabilities needed to operate in real industrial environments — think surface finishing, welding, and protective coating. As an early team member, you'll have meaningful impact from day one, with a clear path to grow into deployment and MLOps responsibilities as the product and stack mature. Equity participation is included. Note: This role is fully on-site in Munich, Germany. Visa sponsorship is not available. What You'll Do• Train and implement deep learning models as a core part of the 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 and edge settings. • Design and run reproducible experiments; track and evaluate results rigorously. What We're Looking ForRequired (dealbreakers): • 1+ year of hands-on experience training deep learning models using Python and PyTorch (academic projects, thesis work, or industry experience all count). • Experience with Docker for model deployment and environment replication. Also required: • Experience deploying trained models to customer or production environments. • Comfort working in a Linux/command-line environment. • Documented results and evaluation metrics from prior model training work. Nice to have: • Experience with ONNX or other model export/interoperability tools. • Familiarity with data versioning tools (e.g., DVC). • Background or strong interest in computer vision or ro