Woven By Toyota5mo ago

Senior / Staff Machine Learning Engineer, Behavior Planning & Prediction

Palo AltoEmployeesenior

Data ScienceOtherStaff Machine Learning Engineer

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Overview

Woven by Toyota is enabling Toyota’s once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others,

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Data ScienceOtherStaff Machine Learning Engineer

Woven by Toyota is enabling Toyota’s once-in-a-century transformation into a mobility company. Inspired by a legacy of innovating for the benefit of others, our mission is to challenge the current state of mobility through human-centric innovation — expanding what “mobility” means and how it serves society.

Our work centers on four pillars: AD/ADAS, our autonomous driving and advanced driver assist technologies; Arene, our software development platform for software-defined vehicles; Woven City, a test course for mobility; and Cloud & AI, the digital infrastructure powering our collaborative foundation. Business-critical functions empower these teams to execute, and together, we’re working toward one bold goal: a world with zero accidents and enhanced well-being for all.

TEAM

The Behavior team at Woven by Toyota tackles autonomy challenges in prediction and trajectory planning. Our work involves a variety of technical hurdles, such as analyzing petabytes of multimodal driving data, solving optimization problems, minimizing latency on hardware accelerators, deploying scalable and efficient machine learning (ML) training and evaluation pipelines, and designing novel neural network architectures to advance state-of-the-art ML for prediction and motion planning. We are looking for driven and creative problem-solvers to join us in improving mobility for everyone through human-centered automated driving solutions for personal and commercial applications.

WHO ARE WE LOOKING FOR?

The Behavior team is searching for a skilled Machine Learning Engineer to support the entire lifecycle of machine learning models. This role involves developing and optimizing machine learning systems, including performance tuning, model development, and developing infrastructure and support systems that facilitate this work. Responsibilities include developing data pipelines, with a focus on transform libraries and dataset management, contributing to metrics and metrics pipelines, and integrating models into our on-vehicle software. This is an opportunity to design and implement innovative machine learning models for our next-generation autonomous vehicle platform, which will impact millions of Toyota production vehicles. We are seeking individuals who are passionate about self-driving car technology and its transformative potential for humanity.

Design and develop advanced machine learning models in the behavior space, specifically tailored for autonomous vehicles, utilizing deep learning and large-scale data analysis.

Deploy scalable and efficient ML models on our autonomous vehicle platform.

Integrate modern technologies with rigorous safety standards while maintaining cost efficiency.

Oversee the development of new ML models end-to-end, from data strategy and initial development to optimization, production platform validation, and fine-tuning based on metrics and on-road performance.

Design, build, and maintain ML pipelines that produce training and evaluation data for behavior and prediction models, including ETL, feature extraction, augmentation, and labeling workflows.

Implement auxiliary pipelines for model validation, metric computation, and on-road performance integration.

Lead large, multi-person projects and significantly influence the overall motion planning architecture and technical direction.

Enable and support other engineers by coaching, leading by example, and providing high-quality code and design document reviews, as well as delivering rigorous reports from ML experiments.

Contribute significantly to the development of essential components for end-to-end ML training and deployment, from data strategy to optimization and validation.

Be a champion of the scientific method and critical thinking to invent state-of-the-art deep learning solutions.

Work in a high-velocity environment and employ agile development practices.

Collaborate closely with teams such as Perception, Simulation, Infrastructure, and Tooling to drive unified solutions.

MS or PhD in Machine Learning, Computer Science, Robotics, or related quantitative fields, or equivalent industry experience.

3+ years of experience with Python, major deep learning frameworks, and software engineering best practices.

Expertise with deep learning approaches, such as supervised/unsupervised learning, transfer learning, multi-task learning, and deep reinforcement learning.

Built robust data pipelines, ETL workflows, and integration systems to support behavior prediction models

Good understanding of learning-based planning approaches, including imitation learning, reinforcement learning, and state-of-the-art techniques for sequential modeling, such as Transformer architectures.

Practical experience with ML training and evaluation workflows, including data sampling, preprocessing, and reproducible experiment management.

3+ years of experience covering machine learning workflows, data sampling and curation, preprocessing, model training, ablation studies, evaluation, deployment, and inference optimization.

Comfortable writing C++ code for integration with our autonomous vehicle platform.

Passion for self-driving car technology and its potential to impact humanity.

Strong communication skills with the ability to articulate concepts clearly and precisely.

Published research at top-tier conferences (NeurIPS, RSS, IROS, ICRA, etc.).

Proven track record of deploying ML models at scale in self-driving or related fields.

Familiarity with production-level coding in time-limited task schedules.

Experience with robot motion planning (e.g., trajectory optimization, sampling-based planning, model predictive control).

Experience working with temporal data and sequential modeling.

Expertise in self-driving challenges (Perception, Prediction, Planning, Simulation).