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ML Engineer
Machine Learning Engineer, Motion Planning

Machine Learning Engineer, Motion Planning

Posted 304 days ago

Job Description

This job posting has expired and no longer accepting applications.

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

Our Motion Planning and Prediction team is looking for a Machine Learning Engineer to contribute to the development of cutting-edge ML models for autonomous vehicle motion planning. In this role, you will focus on researching, developing, and optimizing ML models, helping to integrate learning-based approaches into real-world autonomous systems.

Who are we looking for?

The ideal candidate has hands-on experience with ML frameworks, a solid understanding of imitation learning and deep learning, and a passion for advancing autonomous driving technology.

Responsibilities

Develop and refine ML models for autonomous motion planning, using techniques like imitation learning, deep learning, and large-scale data-driven modeling.

Work on prototyping, validating, and iterating new ML architectures, optimizing performance for real-world deployment.

Contribute to the full ML lifecycle, including data processing, model training, performance evaluation, and deployment on autonomous vehicle platforms.

Collaborate with cross-functional teams (Perception, Simulation, Infrastructure, etc.) to ensure ML models integrate effectively within the broader autonomous driving stack.

Engage in code reviews, experiment documentation, and rigorous model testing to maintain high engineering standards.

Work in an agile, high-velocity environment, contributing to iterative development processes.

Qualifications

Masters or PhD in Machine Learning, Robotics, Computer Science, or related fields.

2+ years of experience with ML frameworks such as PyTorch, TensorFlow, or equivalent.

Knowledge of learning-based planning approaches, including imitation learning, reinforcement learning, and Transformer-based sequential modeling.

Proficient in Python or C++ for ML development and deployment.

Experience in machine learning workflows, including data processing, model training, and inference optimization.

Passionate about autonomous driving and its potential impact on mobility.

Nice to Have

Experience with robot motion planning techniques such as trajectory optimization, sampling-based planning, or model predictive control.

Background in self-driving technologies (Perception, Prediction, Mapping, Localization, Planning, Simulation).

Experience with ML deployment on real-time operating systems.

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.

WHAT WE OFFER

We are committed to creating a modern work environment that supports our employees and their loved ones. We offer many options of the best programs to allow you to do your most meaningful work and to help you shape the future of mobility.

・Excellent health, wellness, dental and vision coverage

・A rewarding 401k program

・Flexible vacation policy

・Family planning and care benefits

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.

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