Foundation Models for Autonomous Driving – AI Engineering Intern

Company Description

The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania and Cambridge, Massachusetts is part of the global Bosch Group (www.bosch.com), a company with over 70 billion euro revenue, 400,000 people worldwide, a very diverse product portfolio, and a history of over 125 years. The Research and Technology Center North America (RTC-NA) is committed to providing technologies and system solutions for various Bosch business fields primarily in the areas of Human Machine Interaction (HMI), Robotics, Energy Technologies, Internet Technologies, Circuit Design, Semiconductors and Wireless, and MEMS Advanced Design.*

As a part of the global research, our AI research in Silicon Valley focuses on Foundation Models, Big Data Visual Analytics, Explainable AI (XAI), Natural Language Processing, Computer Vision & Mixed Reality, Cloud Robotics, Data Science, AI System Engineering, Time-series Analysis. We develop scalable, intelligent, and trustworthy AIoT solutions for Bosch products and services in application areas such as automated driving, advanced driver assistance systems (ADAS), robotics, smart manufacturing, enterprise AI, health care, smart home and building solutions.

Originating from the AI research in Silicon Valley, our Intelligent Autonomous Systems group is responsible for enabling future autonomous Bosch products by developing cutting-edge technologies and prototype systems in the fields of autonomous driving, automation and robotics. These include methods for 3D Perception, knowledge distillation, multimodal learning, and motion prediction/planning as well as systems for making these technologies work on real products by building frameworks that take advantage of technologies in the field of reliable distributed computing. We work with internal partners of different Bosch business units to transfer our solutions into future products. We also actively collaborate with leading groups in academia and industry to promote research ideas and publish research findings in internationally renowned conferences and journals such as CVPR, ICCV, ECCV, ICML, ICLR, and NeurIPS.

We Are Bosch.

At Bosch, we shape the future by inventing high-quality technologies and services that spark enthusiasm and enrich people’s lives. Our areas of activity are every bit as diverse as our outstanding Bosch teams around the world. Their creativity is the key to innovation through connected living, mobility, or industry.

Let’s grow together, enjoy more, and inspire each other. Work #LikeABosch 

• Reinvent yourself: At Bosch, you will evolve.
• Discover new directions: At Bosch, you will find your place.
• Balance your life: At Bosch, your job matches your lifestyle.
• Celebrate success: At Bosch, we celebrate you.
• Be yourself: At Bosch, we value values.
• Shape tomorrow: At Bosch, you change lives.

Do you want beneficial technologies being shaped your ideas? Whether in the areas of mobility solutions, consumer goods, industrial technology or energy and building technology - with us, you will have the chance to improve quality of life all across the globe. Welcome to Bosch.

Job Description

• 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.

Qualifications

Basic Qualifications

• Master’s student 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, diffusion models, detection/segmentation, 3D scene understanding, autonomous driving , and sensor fusion.
• Solid Python skills and proficient with libraries such as MMCV, and PyTorch.

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.
• 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

Start Date: J