About this role
Summary: Develop and optimize machine learning solutions for automated driving and ADAS by processing multimodal sensor data. Implement deep learning models for perception and prediction, collaborate with engineering teams, and validate algorithms for real-time automotive applications.
WHAT TO EXPECT
You will work with large‑scale sensor, vehicle, and fleet data to drive the development, validation, and optimization of automated driving functions. In this role, you will implement and advance innovative, data‑driven software solutions and directly contribute to shaping impactful projects. You will have the opportunity to grow your expertise while collaborating with a motivated, supportive, and highly skilled team.
Please send your documents in English.
YOUR TASKS
YOUR PROFILE
- Develop and implement Machine Learning solutions for Automated Driving and Advanced Driver Assistance Systems (ADAS)
- Analyze and process multimodal sensor data from camera, radar, and LiDAR systems
- Develop, train, and optimize Deep Learning and Computer Vision models for perception, scene understanding, and prediction tasks
- Support the evaluation and integration of modern AI technologies, including Foundation Models, Vision-Language Models, Generative AI, and Edge AI
- Contribute to the development of sensor fusion, perception, and environment modeling solutions for automated driving functions
- Perform technology evaluations, benchmarking activities, and proof-of-concepts based on current scientific research and state-of-the-art methodologies
- Collaborate closely with software developers, systems engineers, and data scientists to integrate AI solutions into automotive applications
- Continuously optimize and validate algorithms with respect to performance, robustness, scalability, and real-time capability
- Improve algorithm performance, robustness, scalability, and real-time capabilities
- Support innovation projects and help transfer emerging research concepts into practical customer solutions and industrial applications
- Successfully completed degree in Computer Science, Artificial Intelligence, Data Science, Robotics, Mathematics, Physics, or a comparable field
- Initial practical experience in Machine Learning, Deep Learning, Computer Vision, or AI through internships, research projects, theses, or working student positions
- Good knowledge of Python and ideally first experience with C++, Rust, or SQL
- Experience with modern AI frameworks and libraries such as PyTorch, Hugging Face, TensorFlow, OpenCV, NumPy, or Pandas
- Basic understanding of modern AI methods and architectures, including Computer Vision, Foundation Models, Vision Transformers, Vision-Language Models, Generative AI, or multimodal systems
- First experience in processing and analyzing camera, radar, or LiDAR data is a plus
- Familiarity with Linux, Git, Docker, cloud platforms, MLOps, Edge AI, or Embedded AI is a plus.
- Passion for AI, Computer Vision, and Automated Driving technologie
- Strong analytical mindset, proactive attitude, and willingness to learn
- German is a plus
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+ 49 (0)89 / 31857-0
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