Foundation Models for Autonomous Driving - AI Engineering Intern

Job Description:

Job Description

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

Candidate Requirements:

Qualifications

Basic Qualifications
* Currently enrolled in a PhD or 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
Preferred Qualifications
* 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