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Application Engineer - TwinCAT Machine Learning - Beckhoff Automation GmbH & Co. KG
ML Engineer
Lead the integration of machine learning models into TwinCAT-based automation systems, optimizing industrial processes through advanced PLC programming and embedded software development.
About the role
Key Responsibilities
- Design, develop, and deploy machine learning solutions within TwinCAT environments to enhance automation performance.
- Collaborate with cross‑functional teams to translate business requirements into PLC and embedded software specifications.
- Implement and validate C/C++ and Python code for real‑time data acquisition, preprocessing, and inference on edge devices.
- Conduct performance tuning, debugging, and continuous improvement of ML models and control logic.
- Document architecture, code, and test procedures to support maintenance and knowledge transfer.
Requirements
- Strong experience with TwinCAT PLC programming and automation concepts.
- Proficiency in C/C++ and Python for embedded and ML application development.
- Hands‑on knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) and model deployment strategies.
- Solid understanding of real‑time systems, signal processing, and data pipelines.
- Excellent problem‑solving skills and ability to work independently in a fast‑paced environment.
Skills
machine learningpython