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For our Smart Accessories Team, we are looking for a Machine Learning Engineer - Computer Vision & Edge AI to strengthen our agile team. We are seeking an engineer who thoroughly understands deep learning and computer vision architectures and is ready to take on hands-on development, diagnostic, and optimization tasks.
This position can be filled on a hybrid basis. Regular in-person work in Landsberg am Lech is required.
Key Responsibilities
- Together with the team, you drive the development and evolution of vision systems
- You understand, evaluate, and challenge model architectures, neural networks, inference pipelines, and diagnostic toolchains, gradually taking over dedicated development and optimization work packages
- You oversee the integration, validation, benchmarking, and diagnostics of ML models on our embedded target hardware and define robust performance and accuracy metrics
- You support the entire data and model lifecycle – from data collection, curation, and annotation pipelines to evaluation, edge benchmarking, and edge-case error analysis
- You collaborate closely with our embedded software engineers, cloud developers, and the Product Owner to seamlessly integrate vision capabilities into the broader product architecture
Qualifications
If you do not meet all requirements or would like to develop towards this exciting field, we still encourage you to apply. We work pragmatically as a team and provide everything you need to quickly become familiar with the topic.
- You have a degree in Computer Science, Data Science, Electrical Engineering, Physics, Mathematics, or a comparable field with a focus on Machine Learning / Computer Vision
- Proven practical experience in computer vision and deep learning using frameworks such as PyTorch, TensorFlow, OpenCV, or ONNX
- Solid understanding of edge AI and inference optimization on embedded devices (e.g., quantization, pruning, ONNX Runtime, TensorRT, OpenVINO, NPU/VPU/DSP accelerators)
- Solid programming skills in Python and modern C++ (C++17 or newer) for integrating vision pipelines into embedded software environments
- Experience in model diagnostics, validation metrics, and data curation pipelines (data gathering, labeling, augmentation)
- Experience working with external technology partners or suppliers is an advantage
- Familiarity with standard software development tools (e.g., Git, GitLab/GitHub, Docker/containers, Linux)
- Analytical, self-driven, and structured approach with enthusiasm for agile collaboration in a Scrum team
- Very good English skills (C1) and German skills are an advantage