Students / Trainees

Location: Garching - Bavaria, Germany - Parking 1-5 Business Campus Job Family: General & Administration Worker Type Reference: Intern (Fixed Term) (Trainee) - Intern Pay Rate Type: Hourly Career Level: U0 Job ID: R-56669-2026 ### **Description & Requirements** **„** **Master Thesis: E2E AI model deployment and Closed loop Framework, ADAS Lab (m/w/d)“** **About the position:** * The objective is to develop and validate a hardware-aware, closed-loop AI solution for urban automated driving. You will investigate how an existing end-to-end driving model can be efficiently deployed on a new automotive system-on-chip (SoC) and evaluate its behavior in realistic, near-real-time driving scenarios using a simulation environment. **Your team:** * Work in the TPP team within the ADAS Lab at Harman’s Garching office. **Your responsibilities:** * Model Deployment, Profiling, and Optimization + Port an existing end-to-end driving model to an Automotive platform under Linux. + Profile model execution at system, layer, and operator level. + Analyze compute-engine allocation, memory behavior, bandwidth usage, latency, and performance bottlenecks. + Investigate operator placement across CPUs and NPUs, custom operators, data orchestration, and other deployment optimizations. + Explore hardware-aware model and operator designs suitable for future automotive SoCs. + Derive practical recommendations for building accurate models that satisfy real-time execution and memory-bandwidth constraints. * Reinforcement Learning and Closed-Loop Validation + Review the current SIL and HIL-Framework for closed-loop simulation environment. + Add reinforcement-learning train and evaluation methods to the SIL closed loop environment. + Measure driving behavior, system performance, and end-to-end output latency. + Generate internal simulation data. + Define the reinforcement-learning algorithm, reward function, and training procedure together with the supervisors as part of the final thesis scope. **Your skills / qualifications:** * You are pursuing a master's degree in computer science, electrical engineering, robotics, automotive engineering, or a related field. * You have a strong interest in automated driving, embedded AI, or machine learning deployment. * You have practical experience with Python and a deep-learning framework such as PyTorch. * You understand neural networks, model inference, and performance evaluation. * Ideally, you have experience with reinforcement learning, Linux, automotive simulation, heterogeneous computing, or embedded accelerators such as NPUs. * You work independently, approach technical problems systematically, and communicate your findings clearly. **What we offer:** Flexible working time Training on the job from experts, and access to learning materials Above average payment Experiences and passion in a global acting team **About HARMAN: Where Innovation Unleashes Next