Senior Machine Learning Engineer (m/f/d) Computer Vision for Robotics
Senior machine learning engineer designing and training deep-learning models in PyTorch for visual servoing in precision robot manipulation. Day-to-day: building 2D/3D perception (pose, depth, tracking), integrating models into closed-loop robot control, evaluating on real robots, and deploying real-time C++/Python inference pipelines optimized with ONNX, TensorRT, and CUDA.
- Compensation
- Not disclosed
- Location
- Munich, Bavaria, Germany
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ml / AI
- Posted
Skills
Must have
- Master's or PhD in computer science, robotics, electrical engineering, or related field, or equivalent research/industry experience
- 3+ years of experience in machine learning, computer vision, or robotics
- Hands-on experience designing, training, and tuning deep-learning models end to end in PyTorch
- Experience adapting, combining, or extending existing ML or vision methods for new tasks
- Solid understanding of computer vision and 2D/3D geometry
- Software development in Python with working knowledge of C++
Nice to have
- Understanding of robot kinematics, feedback control, visual servoing, or high-precision manipulation
- Experience deploying optimized models with ONNX, TensorRT, or comparable frameworks, including on embedded or industrial GPU platforms
- Familiarity with reinforcement learning or imitation learning
- Experience with industrial 2D/3D cameras, lens models, camera calibration, or point clouds
- Experience with ROS or ROS 2
Full description
The AI Teams at Agile Robots are looking for a SeniorMachine Learning Engineer (m/f/d) Computer Vision for Robotics, who will design and train deep-learning models for visual servoing in precision robot manipulation. Your model's output steers the robot as it moves, so inference latency and sub-millimetre accuracy both decide whether the task succeeds.
Responsibilities
- Method Development: Develop deep-learning methods for visual servoing and robotic vision, adapting and combining existing methods for new tasks where that requires significant changes.
- Model Training: Design, train, fine-tune, and evaluate models in PyTorch, including adapting pretrained and foundation models to real robot tasks.
- Perception Methods: Develop 2D and 3D perception for pose estimation, depth, tracking, and geometric understanding, combining learned, classical, and optimization-based methods where each fits.
- Closed-Loop Integration: Integrate learned models into closed-loop robot control for high-precision manipulation.
- Robot Evaluation: Evaluate models on real robots and precision manipulation tasks, analyse failure cases, and improve robustness and generalization.
- Real-Time Deployment: Build real-time inference pipelines in C++ and Python and optimize models with ONNX, TensorRT, and CUDA to meet the timing of the control loop.
Essential Skills
- Background: Master's degree or PhD in computer science, robotics, electrical engineering, or a related field, or an equivalent combination of research and industry experience, with three or more years in machine learning, computer vision, or robotics.
- ML Pipeline: Hands-on experience designing, training, and tuning deep-learning models end to end in PyTorch.
- Method Development: Experience adapting, combining, or extending existing machine learning or vision methods for a new task, with changes that required understanding how those methods work internally.
- Computer Vision: Solid understanding of computer vision and 2D/3D geometry.
- Programming: Software development in Python, with working knowledge of C++.
Beneficial Skills
- Robot Control: Understanding of robot kinematics, feedback control, or visual servoing, or experience with high-precision manipulation. The team supports candidates in building this experience on the job.
- Model Deployment: Experience deploying optimized models with ONNX, TensorRT, or comparable frameworks, including on embedded or industrial GPU platforms.