Autonomous Driving Machine Learning Engineer (Behavior Planning)
Sunnyvale, CA
Applications have closed
Mercedes-Benz R&D North America
The role will start with triaging our current fleet of highly automated vehicles and eventually advance into developing the future generation of the Mercedes-Benz ADAS system in the Parking Software Development team. The team works in the field of near field Perception, Fusion, Planning and Localization. Advanced driver assistance and autonomous driving systems (SAE levels 2-4) for urban and highway driving are the focus. The Parking Software Development team is part of the Autonomous Driving team at MBRDNA and part of the global Mercedes-Benz R&D development team. Major contributions of the team are overall architecture, design, functional algorithms, embedded driving software of our development and customer vehicles as well as tools and processes necessary for successful software development and verification & validation.
Job Responsibilities:
- Triage and analyze recorded measurements from a fleet of highly automated vehicles
- Develop robust real-time algorithms in context of situation analysis, decision making, behavior and motion planning for autonomous vehicles
- Develop an efficient architecture for autonomous vehicles
- Optimize, test and validate the developed algorithms and software in order to make it suitable for production vehicles without a safety driver
- Maintain and document code to keep colleagues up-to-date with the quickly-evolving software
Minimum Qualifications:
- Bachelor's degree in Computer Science, Robotics, or related fields
- Proficient programming skills in C++ and some scripting language (e.g. Python)
- Solid knowledge of graph search algorithms, path planning algorithms, and motion planning algorithms
- Proficient knowledge in general software engineering (code design, patterns, source code versioning tools such as git)
- Background in Machine Learning and Deep Learning concepts and algorithms
- Hands-on experience with deep learning frameworks such as Tensorflow, PyTorch, Caffe
- Proficient with Linux SW development environments
- Experience with developing software in a collaborative environment
- Ability to interact with remote locations over different time zones and create a link between remote locations and Silicon Valley
- Driving a vehicle is required for this position
- Hybrid work in the Sunnyvale office
Why should you apply?Here at MBRDNA, you create digital ecosystems around cars, you design a language between humans and machines, you make a car even more intelligent - you make the new reality for cars. We have an open and flexible environment to allow you to push boundaries, join MBRDNA and design your future.
Benefits for Full-Time* Employees Include: • Medical, dental, and vision insurance for employees and their families • 401(k) with employer match • Up to 18 company-paid holidays • Paid time off (unlimited for salaried employees), sick time, and parental leave • Tuition assistance program • Wellness/Fitness reimbursement programs • Vehicle lease subsidy or company car (for eligible employees only)
* Internships excluded from Full-Time Employee benefits
MBRDNA is an equal opportunity employer (EOE) and strongly supports diversity in the workforce. MBRDNA only accepts resumes from approved agencies who have a valid Agency Agreement on file. Please do not forward resumes to our applicant tracking system, MBRDNA employees, or send to any MBRDNA location. MBRDNA is not responsible for any fees or claims related to receipt of unsolicited resumes.
Mercedes-Benz Research and Development North America, Inc.PRIVACY NOTICE FOR CALIFORNIA RESIDENTShttps://mbrdna.com/california-employee-privacy-notice/
Tags: ANN Architecture Autonomous Driving Caffe Computer Science Deep Learning Engineering Git Linux Machine Learning Privacy Python PyTorch R R&D Research Robotics TensorFlow Testing
Perks/benefits: 401(k) matching Career development Fitness / gym Flex vacation Health care Medical leave Parental leave Startup environment Unlimited paid time off Wellness
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