Robotics AI Engineer

Responsibilities

• Identify existing and new processes suitable for automation using artificial intelligence (especially machine learning), machine vision, robotics, or combinations of these domains. Define and further develop a standardized evaluation logic for this purpose.

• Select technologies suitable for automation (camera systems, robots, algorithms, software frameworks or software packages). Conduct global market analyses or startup screenings and prepare decision proposals.

• Implement prototypes of the new processes and develop applications (software development, programming). Use existing open-source algorithms and software frameworks, then test and optimize the application.

• Evaluate prototypes with respect to functionality, economic potential, and scalability to similar processes or transfer to other production sites. If assessment is positive, hand over to the relevant production-site teams for implementation. Our team will provide technical support during implementation.

• Contribute to research projects / publicly funded projects in the field of industrial applications of artificial intelligence combined with machine vision and (humanoid) robotics.

• Maintain the internal production-technology network for Daimler Truck AG. This includes organizing regular meetings with colleagues from production sites to exchange information and document ongoing activities in the aforementioned technology areas.

Qualifications

• Master’s degree in Computer Science, Robotics, Mechatronics, or a related field.

• Experience contributing to relevant research projects or research institutions, or participation in comparable industrial projects (areas: machine learning, computer vision, robotics).

• Practical experience in implementing systems for intelligent robot control using video images or other sensor data via neural networks (programming, training neural networks, optimization methods).

• Programming skills: Python, C++, ROS.

• Computer vision: filters, feature extraction, point cloud analysis.

• Neural networks (CNNs): transfer learning, frameworks (e.g., TensorFlow, YOLO, etc.).

• Robotics: programming, basic knowledge of mechanics and kinematics.

• Languages: business-fluent English; ideally an additional foreign language.