Principal Scientist – Machine Learning for Autonomous Driving Behavior

Job title: Principal Scientist – Machine Learning for Autonomous Driving Behavior

Company: Bosch

Job description: Company Description

Robert Bosch LLC is an international, non-profit-owned company with roughly $85B in 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 automated driving products that are already saving lives on the road and future generations, and to conduct peer-reviewed research collaborations with UT Austin and other top academic institutions that focus on any level of autonomous driving systems.

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.

Job Description

Robert Bosch LLC is looking for a principal scientist at our Austin, TX location. The site is embedded in the University of Texas at Austin’s Computer Science Department (TXCS), with offices in the CS Department’s beautiful new Gates Dell Complex. In this unique set-up, Bosch Austin employees will also be given TXCS visiting researcher status and will closely collaborate with Profs. Peter Stone and Scott Niekum, as well as their research groups.

This position includes management and technical responsibilities for the development of Automated Driving (AD) algorithms.

As the principal scientist, your initial tasks will include co-leading the creation and set-up of a software and algorithm research and development team for AD.

In addition, you will be responsible for the scoping, supervision, and publication of peer-reviewed research projects; and work in close collaboration with our global development team including researchers, software developers and project managers to derive project specific solutions for automated driving technologies.

The ideal candidate has a proven background in robotics, artificial intelligence, and computer science, excellent software skills, with a strong publishing record in reinforcement learning or imitation learning, and a successful track-record in both fundamental research and applied R&D settings.

Responsibilities

• Hire, grow, and nurture a highly competent software algorithm team
• Lead 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 and leading applied topics.
• Guide development of cutting-edge algorithms in the robotic domains of path planning, decision making, perception, sensor data fusion and localization.
• Provide technical leadership to the engineering project team.
• Collaborate with faculty and students at UT Austin and beyond to solve open research questions of automated driving.
• Become part of the UT Austin Computer Science community, attending research group meetings and lectures as well as discussing ideas with university colleagues.
• Create and share technical documentation with sister teams located in the US and worldwide.
• Monthly reporting of project status to management in US and Germany.

Qualifications

Basic Qualifications:

• PhD with a focus on robotic learning, reinforcement learning, imitation learning, or planning for navigation.
• Strong publication history in related fields.
• Widely networked with other researchers in related fields.
• 2+ years managerial experience as team or group leader.

Preferred Qualifications:

• Strongly preferred: Expert in general software development within complex system architectures.
• Strongly preferred: 3+ years of experience programming in C++ or Python in the context of machine learning development.
• Strongly preferred: Experience designing and implementing deep learning algorithms for sequential decision-making.
• Strongly preferred: Excellent communication skills, both written and verbal
• Industry R&D experience in a related field.
• 2+ years of experience managing complex software and system architectures.
• 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.

Additional Information

All your information will be kept confidential according to EEO guidelines.

Expected salary:

Location: Austin, TX

Job date: Fri, 10 Sep 2021 06:34:04 GMT


More info

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