Woven by Toyota

Engineering Manager, Motion Planning

Woven by Toyota

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

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Salary

💰 $140,000 - $230,000 per year

Job Level

Mid-LevelSenior

Tech Stack

CloudPythonRTOS

About the role

  • Lead a team of engineers in the Planner Feature Integration and Core Development team, leveraging both technical expertise and leadership skills to drive high-impact results.
  • Define the team's short-term and long-term technical direction while collaborating on broader, cross-functional strategic initiatives.
  • Expand the team through strategic hiring and support the ongoing professional development of team members.
  • Collaborate with team members to design, develop, deploy, and evaluate state-of-the-art algorithms and capabilities for vehicle motion planning.
  • Collaborate with team members to integrate the machine learning model in the motion planning stack.
  • Use metrics to measure, validate, improve performance through testing in simulation and on roads.
  • Design reusable software components as part of an integrated system.
  • Understand and fulfill the software practices that produce maintainable code, including simulation, continuous integration, code review, HIL testing, and in-vehicle testing.

Requirements

  • M.S., Ph.D., or equivalent, in Robotics, Control, Computer Science, Applied Mathematics, or other quantitative fields.
  • 5+ years of professional experience in the automotive industry, in the development of motion planning algorithms, e.g. trajectory optimization, sampling-based planning, model predictive control, and machine learning.
  • 2+ years of experience in managing engineering teams, with a focus on technical leadership, team development, and delivering high-impact projects in the automotive industry.
  • Hands-on experience with architecture design and building a planning stack for autonomous robots.
  • Strong programming skills in C++.
  • An excellent communicator, skilled collaborator, and principled colleague.
  • Strong R&D potential in algorithm design, data-driven approaches to safety, and large-scale systems architecture.
  • A strong, practical understanding of real-time system development, performance issues, testing modalities, and tradeoffs.