Additionalinformation

Additional Information

Equal Opportunity Employer, including disability / veterans

*Bosch adheres to Federal, State, and Local laws regarding drug-testing. 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.

BOSCH is a proud supporter of STEM (Science, Technology, Engineering & Mathematics)

• FIRST Robotics (For Inspiration and Recognition of Science and Technology)
• AWIM (A World In Motion)

The U.S. base salary range for this intern position is $46.00-69.00 hourly. Within the range, individual pay is determined based on several factors, including, but not limited to, type of degree, work experience and job knowledge, complexity of the role, type of position, job location, etc. Your Hiring Manager can share more details about the specific salary range for this position during the interview process.

For more information on our culture and benefits, please visit:

Culture and Benefits | Bosch in the USA

Companydescription

Company Description

The Bosch Research and Technology Center North America with offices in Sunnyvale, California, Pittsburgh, Pennsylvania, and Cambridge, Massachusetts is a part of the global Bosch Group (www.bosch.com), a company with over 70 billion euro revenue, 400,000 employees worldwide, a very diverse product portfolio, and a history spanning over 125 years. The Research and Technology Center North America (RTC-NA) is dedicated to providing technologies and system solutions for various Bosch business fields, primarily in the field of artificial intelligence, energy technologies, internet technologies, circuit design, semiconductors and wireless, as well as advanced MEMS 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 pushing the boundaries of automated driving, advanced driver assistance systems (ADAS), robotics and automation through key innovations that encompass system architecture and AI components. These include methods for motion planning, high level task planning and decision making 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, ICRA, IROS, RSS, NeurIPS and CoRL.

Jobdescription

Job Description

At Bosch Research, you will work on the latest challenges drawn from Mobility, including autonomous parking and driving. You will work closely with experienced Bosch researchers in Silicon Valley and across our global research network, receive mentorship from leading AI experts, and contribute to publications in top-tier AI conferences and journals. This internship offers a unique opportunity to combine scientific innovation with real-world deployment and technology transfer.

Depending on your expertise and interests, you will contribute to one or more cutting-edge research topics, including:

• Autonomous E2E/ World Action Models (WAM) models
• Planning and decision making under uncertainty and noise
• Road user behavior modeling in dynamic scenarios
• Post-training, Reinforcement Learning, and Self-Play
• Foundation model distillation (i.e. student/teacher)
• Multi-modal trajectory modeling using vision and priors

Key responsibilities include:

• Conduct novel research in E2E, Distillation, and RL methods.
• Develop research prototypes that demonstrate innovative ideas and solutions.
• Collaborate closely with Bosch researchers and subject-matter experts.
• Analyze experimental results and identify opportunities for scientific innovation.
• Publish research outcomes in top-tier AI and robotics conferences and journals, such as CoRL, ICRA, CVPR, NeurIPS, ICML, and ICLR.
• Present research findings internally and externally through technical reports, publications, and presentations.

Qualifications

Basic Qualifications

• Currently enrolled in a Ph.D. or Master's program in Computer Science, Computer Engineering, Electrical Engineering, Artificial Intelligence, Robotics, or a related field.
• Minimum GPA of 3.0
• Strong research background in autonomous driving, robotics, computer vision, machine learning, or related areas
• Research experience in post-training, reinforcement learning, self-play, and end-to-end systems.
• Experience developing AI and robotics systems using modern frameworks and ecosystems
• Strong programming skills in Python and experience with modern AI/ML framework
• Experience conducting independent research, designing experiments, and analyzing results.
• Strong written and verbal communication skills and ability to work effectively in a collaborative research environment.

Preferred Qualifications

• Publication record in top-tier AI, CV, or robotics venues (e.g., CoRL, ICRA, CVPR, NeurIPS, ICML, and ICLR).
• Research experience in autonomous driving and robotics architectures, task planning, reasoning, and autonomous decision making.
• Experience with behavior modeling, scene understanding, and prediction
• Experience with multi-modal foundation models involving language, vision, and structured data.
• Experience in reinforcement learning, online learning, or adaptive decision-making systems.
• Experience with autonomous driving benchmarking, evaluation methodologies, reliability, and safety.
• Experience working with real-time systems and full driving/parking/robotics stack(s)
• Open-source contributions or demonstrated leadership in AI research communities.