About The Position

As an engineering intern for foundation model in autonomous driving, you will: Implement cutting edge research methods into efficient and production ready solutions to address challenges in autonomous driving systems. Develop scalable systems to run experiments and benchmarking in real-world applications with high quality implementation. Integrate the resulting system/software into existing Bosch platform. Summarize research findings in high-quality paper and/or patent submissions

Requirements

  • Currently enrolled in a Master’s program in Computer Science or related fields (Must be a current student)
  • Hands-on experience on developing computer vision and machine learning algorithms with focus on at least two of the following areas: multimodal foundation models, vision-language-action models (VLA), diffusion models, detection/segmentation, 3D scene understanding, autonomous driving, and sensor fusion.
  • Solid Python skills and proficient with libraries such as MMCV, and PyTorch.
  • Minimum GPA of 3.0

Nice To Haves

  • Experience with training codebase of popular open-source vision and foundation models.
  • Familiar with SOTA vision and learning methods of multimodal LLMs, diffusion models, Diffusion Models, knowledge distillation, and so on.
  • Experience in training models with reinforcement learning.
  • Able to work independently, has strong research and problem-solving skills
  • Strong background in math and statistics is a plus.
  • Good communication and teamwork skills

Responsibilities

  • Implement cutting edge research methods into efficient and production ready solutions to address challenges in autonomous driving systems.
  • Develop scalable systems to run experiments and benchmarking in real-world applications with high quality implementation.
  • Integrate the resulting system/software into existing Bosch platform.
  • Summarize research findings in high-quality paper and/or patent submissions
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