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Vision-Language-Action Models - Intern

Bosch

Vision-Language-Action Models - Intern

Bosch

Sunnyvale

·

On-site

·

Internship

·

1w ago

As an intern in the field of Vision-Language-Action Models, your responsibilities will be the following:

  • Conduct advanced research on LLMs /VLMs for autonomous driving
  • Design, implement supervised and reinforcement fine-tuning algorithms to optimize LLMs/VLMs for autonomous driving task.
  • Collaborate with mentors and team members to refine research goals, discuss technical challenges, and explore extensions such as closed-loop fine-tuning and RL integration.
  • Regularly report research progress through meetings, written updates, and technical presentations.
  • Analyze experimental results, document methodologies, and summarize findings in clear and reproducible formats.
  • Contribute to the preparation of research papers, technical reports, or potential submissions to top conferences

Basic Qualifications

  • Ph.D. student in Computer Science, Robotics or related fields.
  • Hands-on experience on developing algorithms with focus on at least two of the following areas: multimodal foundation models, 3D scene understanding, autonomous driving , reinforcement learning and robotic navigation or planning.
  • Solid Python skills and proficient with libraries such as Py Torch.
  • Minimum GPA of 3.0

Preferred Qualifications

  • Publication record in top venues including CVPR, ICCV, ECCV, ICLR etc.
  • Familiar with CARLA or Nav Sim
  • Able to work independently, has strong research and problem-solving skills
  • Good communication and teamwork skills

The U.S. base salary range for this intern position is $39.00 - $64.00. 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.

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

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

*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.

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.

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About Bosch

Bosch

Bosch

Public

Robert Bosch GmbH is a multinational engineering and technology company that develops automotive components, industrial technology, consumer goods, and energy solutions. The company operates across multiple sectors including mobility solutions, industrial technology, consumer goods, and building technologies.

10,001+

Employees

Gerlingen

Headquarters

Reviews

3.7

10 reviews

Work Life Balance

3.2

Compensation

3.8

Culture

4.1

Career

4.3

Management

2.9

72%

Recommend to a Friend

Pros

Great people and team environment

Career development and learning opportunities

Good compensation and benefits

Cons

Poor work-life balance expectations

Management issues and favoritism

Lack of clear policies

Salary Ranges

711 data points

Junior/L3

Mid/L4

Senior/L5

Director

Junior/L3 · Controls Systems Engineer

5 reports

$114,713

total / year

Base

$99,750

Stock

-

Bonus

-

$103,500

$117,300

Interview Experience

7 interviews

Difficulty

2.4

/ 5

Duration

14-28 weeks

Offer Rate

71%

Experience

Positive 14%

Neutral 86%

Negative 0%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Interview Round 1

4

Technical Interview Round 2

5

HR Round/Salary Negotiation

6

Offer Extended

Common Questions

Technical Knowledge

Coding/Algorithm

Behavioral/STAR

Past Experience

Project-based Assessment