Senior ML & Robotics Engineer | Autonomous Driving & Computer Vision Expert

Machine Learning & Deep Learning
Extensive expertise in designing and implementing end-to-end ML training pipelines, including deep learning architectures such as CNNs, LLM-based Agentic workflows, Diffusion Policies, and Reinforcement Learning. Application of frameworks like PyTorch, scikit-learn, and MLFlow for model training, evaluation, and deployment in production environments.

Computer Vision
Broad experience in developing computer vision algorithms for automotive and robotics applications, including 2D/3D Body Pose Tracking, Seat Occupancy detection, Optical Self-Diagnosis, camera calibration, and object detection. Proficient with OpenCV, Voxel51, GStreamer, and ONNX.

Autonomous Driving Algorithm Development
Proven track record in developing and unit-testing algorithms for autonomous driving systems, including sensor fusion, radar data processing, ML trajectory prediction, Driving Tube Vehicle estimation, and clothoid-based estimation algorithms. Tools used include C++, Bazel, AWS, Foxglove/MCAP, and Zuul.

MLOps & Synthetic Data Pipelines
Design and implementation of scalable MLOps pipelines and synthetic data workflows using Nvidia Isaac Sim, Weights & Biases, and Voxel51 for autonomous physical AI systems, including full model lineage and experiment tracking.

Robotics & Cognitive Systems
Research and development in cognitive robotics, including visual Reinforcement Learning for 3D object trajectory prediction, robotic manipulation, and integration of machine learning with robotic systems. Experience with ROS 2, LeRobot, and simulation environments.

Software Architecture & Systems Integration
Definition of software architectures and component interfaces within complex automotive operating systems (e.g., Bosch AOS comparable to ROS 2), as well as integration of AI features into embedded and edge systems ensuring low-latency inference.

C++ & Python Software Development
Proficient in C++ and Python for developing production-grade software in automotive and robotics domains. Experience with STL, Qt, OpenGL, Nvidia PhysX, CUDA, and various build systems including Bazel, CMake, and Jenkins.

Explainable AI (XAI)
Advancement of transparency in internal AI models through extension of the eXplainable AI (XAI) framework at Robert Bosch GmbH, contributing to a patent-pending invention in the field of camera calibration.

Team Leadership & R&D Management
Leadership of a 10-person R&D team at Adasens Automotive GmbH, overseeing technical execution, performance reviews, and full-cycle implementation of ADAS systems from Proof of Concept to series production.

Sensor Fusion & Radar Data Processing
Delivery of sensor fusion, radar data processing, and ML trajectory prediction algorithms for series production vehicles at major OEMs including Daimler, BMW, and Toyota. Implementation of Kalman filters and advanced association algorithms.