Research Intern – AI-based Planning for Autonomous Driving

  • Intern
  • Legal Entity: Robert Bosch LLC

Company Description

Robert Bosch North America is part of the global Bosch Group (, a company with over 70 billion euro revenue, 400,000 people worldwide, a very diverse product portfolio, and a history of over 125 years. Best known to consumers for its appliances and power tools, Bosch also happens to be one of the largest automotive supplier in the world, with its vehicle subsystems in nearly 100% of vehicles being made today. Bosch already sells or is developing every sensor and in-car computer required for an autonomous vehicle and has advanced projects at various levels of autonomy, from driverless Level 4 down to driver assistance products that are already in production vehicles.

Our Austin site hosted within the Computer Science department at the University of Texas at Austin offers an R&D experience that's heavy on the R. We have the flexibility to apply AI to Bosch's autonomy projects, and to conduct peer-reviewed research collaborations with UT and other top academic institutions that focus on any level of automated driving systems. In short, we find and work on high-impact automated driving problems at Bosch that have not necessarily been viewed yet through the lens of an AI researcher.

Job Description

If selected, you will be part of our site embedded in the University of Texas at Austin's Computer Science Department, with offices in the CS Department's beautiful new Gates Dell Complex. As part of your application process, we will together find a research project for you to work on during the period of the internship. Depending upon your interests and experience, your research project could either be collaborative research towards a peer-reviewed publication or applied R&D that contributes to Bosch's autonomous driving projects.

We want to hear from you if you have begun publishing in reinforcement learning or learning from demonstration, enjoy collaborating and communicating about your work, and are comfortable moving between settings of fundamental research and applied R&D.


  • One or more of the following: (1) Collaborate on research projects involving the usage of AI to improve the decision making of state-of-the-art autonomous driving and driver assistance systems. Research activities will span collaborating on fundamental topics---where autonomous driving may only be one application of your work---and applied topics. (2) Contribute to the development, implementation, or evaluation of algorithms that can be applied to existing Bosch autonomous driving projects, including adapting research code to be application compatible. (3) Support fundamental research project(s) through software design and programming
  • Contribute to the writing and publication of peer-reviewed research

Become part of the UT Austin Computer Science community, attending research group meetings and lectures as well as discussing ideas with university colleagues.


Required Qualification:

  • Currently pursuing a MS or Ph.D with a focus on robotic learning, reinforcement learning, learning from demonstration / behavioral cloning / imitation learning, or planning for navigation.
  • Must be currently enrolled in an accredited university.
  • Currently pursuing MS or PhD in Statistics, Computer Science or a related technical field.
  • Strong foundations in machine learning.
  • Experience with working on large data sets in a distributed computing environment.
  • Proficient in programming in python / R or other numerical computing languages.
  • Good coding practices, ability to write efficient, readable and error free code.
  • Be enthusiastic and able to collaborate in a team environment.
  • Ability to translate technical concepts into simple to understand, communicable ideas.
  • Curious and passionate about learning everything.

Desired Qualification:

  • Strongly preferred: Excellent communication skills, both written and verbal
  • Strongly preferred: Adept at C++ or Python programming in the context of machine learning development
  • Strongly preferred: Publication record in top venues in robotics/machine learning/computer vision, e.g., ICRA, IROS, RSS, NeurIPS, ICML, ICLR, CVPR, ICCV, and ECCV.
  • Hands-on experience designing and implementing deep learning algorithms for sequential decision-making on physical robots.
  • Knowledge of common automated-driving algorithms, including algorithms for perception and behavior generation.
  • Knowledge of driver assistance technologies.
  • Background in methods for planning under uncertainty and risk-aware intelligent decision making in uncertain environments.
  • Background in probabilistic robotics.
  • Knowledge of Linux, and development on Linux systems.
  • Experience working with big data and associated distributed processing tools (e.g., Spark) as well as cloud services (e.g., AWS, Azure).

Additional Information

The U.S. base salary range for this intern position is $37.00-$56.50. 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.

By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled.

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)
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