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Senior Motion Planning Engineer, ML Integration

Woven by Toyota
Ann Arbor, MI Other
POSTED ON 1/28/2025
AVAILABLE BEFORE 3/27/2025

Woven by Toyota is the mobility technology subsidiary of Toyota Motor Corporation. Our mission is to deliver safe, intelligent, human-centered mobility for all. Through our Arene mobility software platform, safety-first automated driving technology and Toyota Woven City — our test course for advanced mobility — we’re bringing greater freedom, safety and happiness to people and society. 


Our unique global culture weaves modern Silicon Valley innovation and time-tested Japanese quality craftsmanship. We leverage these complementary strengths to amplify the capabilities of drivers, foster happiness, and elevate well-being.


TEAM

At Woven by Toyota, we work on a diverse set of problems ranging from solving Trajectory Planning and Decision Making problems, to optimizing latency on hardware accelerators, designing novel neural network architectures, and applying and advancing the state-of-the-art of machine learning for perception, prediction, and motion planning. We are looking for doers and creative problem solvers to join us in improving mobility for everyone with self-driving technology. You will be interacting on a daily basis with other researchers, software, and hardware engineers to tackle some of the most challenging problems in AI and Robotics.


WHO WE ARE LOOKING FOR?

The team is looking for an experienced Motion Planning Engineer to join us in developing a state-of-the-art machine learning motion planner for autonomous driving. As an expert in machine learning in the Motion Planning team, you will be responsible to integrate ML models in the motion planning stack. You will also contribute to the design and development of our hybrid planner by leveraging the strength of data driven and rule-based approaches to improve our next-generation autonomous vehicles. The ideal candidate will have domain expertise in motion planning, be familiar with machine learning solutions, have built and deployed real-world deep learning products, and have worked in a fast-paced environment along with other highly talented engineers. 


We recognize the unique capabilities each team member brings, and encourage applicants to reach out even if they do not match all of the characteristics described below.


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RESPONSIBILITIES
  • Integrate and deploy ML models in motion planning stack
  • Design experiments to validate model accuracy, robustness, and reliability.
  • Revise the Planner stack design
  • Triage failures and propose suggestions by leveraging large-scale datasets and state-of-the-art techniques to improve model performance.
  • Collaborate with cross-functional teams to ensure seamless integration of ML models.
  • Stay updated with the latest advancements in ML and motion planning to continuously improve our systems.


EXPERIENCE
  • Python and C for integration and deployment of ML models into a production stack.
  • Expertise with any major deep learning framework and software engineering best practices.
  • Motion planning algorithm development for autonomous vehicles or robots. 
  • Computational geometry and linear algebra methods.
  • Strong problem-solving skills and the ability to work in a collaborative, fast-paced environment.
  • Education: Bachelor’s, Master’s or PhD (preferred) in Robotics, Computer Science, Engineering, Mechanical Engineering, or related field.


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For California: The base pay for this position ranges from $112,000-$184,000 a year


Your base salary is one part of your total compensation. We offer a base salary, short term and long term incentives, and a comprehensive benefits package. The total compensation offered to an employee will be dependent upon the individual's skills, experience, qualifications, location, and level.


Our Commitment

・We are an equal opportunity employer and value diversity.

・Any information we receive from you will be used only in the hiring and onboarding process. Please see our privacy notice for more details.

Salary : $112,000 - $184,000

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