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Machine Learning Engineer, Robotics - Analog Devices
ML Engineer
Lead the design and deployment of AI models for robotic systems, integrating Python, C++, and ROS to deliver edge‑optimized solutions that enhance automation and intelligent interaction.
About the role
Key Responsibilities
- Develop and train machine learning models for robotic perception, control, and decision‑making using Python and TensorFlow/PyTorch.
- Implement real‑time inference pipelines on embedded platforms, optimizing for latency and power consumption.
- Collaborate with hardware and firmware teams to integrate AI algorithms into ROS‑based robotic stacks.
- Design and maintain data pipelines for sensor fusion, labeling, and continuous model improvement.
- Conduct performance benchmarking, profiling, and model compression to meet edge deployment constraints.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Robotics, or related field.
- 3+ years of experience in machine learning engineering for robotics or autonomous systems.
- Proficiency in Python, C++, and ROS; experience with TensorFlow or PyTorch.
- Strong understanding of computer vision, SLAM, or control theory is a plus.
- Excellent problem‑solving skills and ability to work cross‑functionally in a fast‑paced environment.
Skills
pythonmachine learningcrostensorflow