Research Engineer - Machine Learning for Autonomous Driving Behavior
- University of Texas at Austin Campus, Austin, TX, United States
- Legal Entity: Robert Bosch LLC
Robert Bosch LLC is an international, non-profit-owned company with ~$85B revenue per year. Many know it best for its appliances and power tools, but Bosch also happens to be the largest automotive supplier in the world, with its vehicle subsystems in nearly 100% of vehicles being made today. Bosch offers just about every subsystem that goes into a car today, from windshield wipers to engine control units. It already sells or is developing every sensor and in-car computer required for an autonomous vehicle. Bosch has advanced projects at various levels of autonomy, from driverless Level 4 down to driver assistance products that are already in production vehicles, such as automatic emergency braking and lane-keep assist.
The Austin office offers an R&D experience that's heavy on the R. We have the flexibility to apply machine learning to existing driver assistance products that are already saving lives on the road, to apply it to Bosch's full autonomy projects, and to conduct peer-reviewed research collaborations with UT Austin and other top academic institutions that focus on any level of autonomous driving systems.
We pay competitive salaries in a vibrant city that's comparatively affordable to live in. *We are dedicated to creating a diverse Austin team and a family-friendly work culture.*
In short, we find and work on high-impact autonomous driving problems at Bosch that have not necessarily been viewed yet through the lens of a machine learning researcher.
If hired, you will be our first research engineer at the new Bosch Austin site. The site is embedded in the University of Texas at Austin's Computer Science Department, with offices in the CS Department's beautiful new Gates Dell Complex.
You will conduct applied R&D and contribute software to Bosch autonomous driving platforms. You will also collaborate with UT Austin researchers on peer-reviewed research and associated publications. And you will work with us to identify projects that are a strong fit for our group.
We want to hear from you if you are adept at bridging between fundamental research results and specific applications of those results, can lead an R&D team on the core software development aspects of its work, enjoy collaborating and communicating about your work, and are comfortable moving between settings of fundamental research and applied R&D.
- Collaborate on research projects involving the usage of machine learning to improve 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 leading applied topics.
- Develop, implement, and evaluate algorithms that can be applied to existing Bosch autonomous driving projects
- Support fundamental research projects 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
- Become an expert on the application to projects within Bosch of machine learning for decision making, including adapting research code to be application compatible
- Graduate degree with a focus on robotic learning, reinforcement learning, learning from demonstration / behavioral cloning / imitation learning, or planning for navigation
- PhD in one of the fields listed above
- Strongly preferred: Excellent communication skills, both written and verbal
- Strongly preferred: Expert in general software development within complex system architectures and varied toolsets
- Strongly preferred: Adept at C++ or Python programming in the context of machine learning development
- Strongly preferred: Past publication in related fields
- Widely networked with other researchers in related fields
- Experience designing and implementing deep learning algorithms for sequential decision-making
- Industry R&D experience in a related field
- Knowledge of common automated-driving algorithms, including algorithms for perception and behavior generation
- Knowledge of driver assistance technologies
- More general expertise in automotive systems: experience with vehicle and system test-release procedures in automotive or related industries; experience in embedded automotive systems; and understanding of vehicle architecture and vehicle interfaces
- Experience testing algorithms on real vehicles
By choice, we are committed to a diverse workforce - EOE/Protected Veteran/Disabled.
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)