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Bosch Home Comfort USA Logo

Automated Driving Intern - Simulation at Scale for RL

Bosch Home Comfort USA

$42 - $58
Sep 17, 2025
Sunnyvale, CA, US
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Bosch is looking to solve challenges in planning and simulation for autonomous driving contexts by applying deep learning and reinforcement learning.

Requirements

  • Currently pursuing MS or PhD in Computer Science / Robotics / Systems Engineering or a related technical field, with research focus on high-performance simulation, reinforcement learning, robotic systems, or autonomous driving applications.
  • Hands-on experience in deep learning and/or AI system topics with focus on at least two of the following areas: reinforcement learning, vector/point-based input representations for learning, planning for navigation, multi-agent training / self-play, and autonomous driving.
  • Programming experience in C++, Python, and hands-on experience with libraries such as PyTorch, CUDA, Tensorflow, etc.
  • 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
  • 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.

Responsibilities

  • Participate in cutting-edge 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.
  • Collaborate with a team of domain experts on novel approaches to learning-based planning and decision-making.
  • Benchmark, validate, and iterate on models using large-scale simulation and datasets.
  • Communicate research findings through internal reports and/or external publications.
  • Build and optimize high-performance, scalable simulation environments tailored for reinforcement learning in autonomous driving scenarios.
  • Develop, train, and integrate planning models for autonomous driving using GPU-accelerated simulations to validate and enhance performance in complex scenarios.

Other

  • Minimum GPA of 3.0
  • Strong leadership skills with excellent English communication & teamwork skills.
  • Equal Opportunity Employer, including disability / veterans
  • Background check and drug screen required
  • Must be currently pursuing MS or PhD in a related technical field