Automated Driving Intern - Simulation at Scale for RL

The ideal candidate will passionately drive and further advance innovations in the field of reinforcement learning and simulation for planning in autonomous driving. The work includes conducting advanced research and development of novel algorithms and conducting experiments to bring innovation ideas to products.

As an intern you will work closely with a team of researchers and engineers on one of the following areas:

1. GPUaccelerated Simulation for Reinforcement Learning
    Build and optimize highperformance scalable simulation environments tailored for reinforcement learning in autonomous driving scenarios.
2. Integration and Development of MLbased Planning Models
    Develop train and integrate planning models for autonomous driving using GPUaccelerated simulations to validate and enhance performance in complex scenarios.
3. Imitation Reinforcement Learning with SelfPlay
    Develop and improve hybrid learning approaches that combine imitation learning and reinforcement learning with a focus on multiagent selfplay techniques.

Responsibilities include but not limited to:

• Participate in cuttingedge engineering projects applying deep learning and reinforcement learning to tackle challenges in planning and simulation for autonomous driving contexts.
• Work with an international team of experts to transfer the results of advanced research to Bosch business units. Benchmark validate and test research ideas on simulated environments large scale datasets and selfdriving vehicles.
• Collaborate with a team of domain experts on novel approaches to learningbased planning and decisionmaking.
• Benchmark validate and iterate on models using largescale simulation and datasets.
• Communicate research findings through internal reports and/or external publications.

Qualifications :

Basic Qualifications

• Currently pursuing MS or PhD in Computer Science / Robotics / Systems Engineering or a related technical field with research focus on highperformance simulation reinforcement learning robotic systems or autonomous driving applications.
• Handson experience in deep learning and/or AI system topics with focus on at least two of the following areas: reinforcement learning vector/pointbased input representations for learning planning for navigation multiagent training / selfplay and autonomous driving.
• Programming experience in C Python and handson experience with libraries such as PyTorch CUDA Tensorflow etc.
• Minimum GPA of 3.0

Preferred Qualifications

• Publication record in top venues in robotics/machine learning/computer vision e.g. ICRA IROS RSS NeurIPS ICML ICLR CVPR ICCV and ECCV.
• Project experience in the field of planning or simulation for automated driving
• Strong leadership skills with excellent English communication & teamwork skills.
• Background in highperformance simulation reinforcement learning or machine learning for autonomous driving.
• Background in probabilistic robotics.
• Experience in writing algorithms in C efficiently and correctly in a production environment (code reviews unit tests etc.)
• Experience with the Madrona engine GPUDrive or other GPU accelerated simulation frameworks.
• Knowledge of Linux and development on Linux systems.

Additional Information :

Equal Opportunity Employer including disability / veterans

The U.S. base salary range for this fulltime position is $42 $58/ HR. Within the range individual pay is determined based on several factors including but not limited to work experience and job knowledge complexity of the role job location etc. Your Recruiter can share more details about the specific salary range for this position during the interview process.

*Bosch adheres to Federal State and Local laws regarding drugtesting. Employment is contingent upon the successful completion of a drug screen and background check. Candidates who have been offered the position must pass both screenings before their start date.

Remote Work :

No

Employment Type :

Fulltime