Engineering Manager, Machine Learning Behavior Planning & Prediction

Woven Planet Holdings Co•Palo Alto, CA

34d•$161,000 - $264,500

About The Position

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 challenges, 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 with human-centered automated driving solutions for personal and commercial applications. WHO ARE WE LOOKING FOR? We are seeking an experienced, technically strong, handsâon Engineering Manager to lead a group of highly talented and passionate engineers on the Behavior team. This role focuses on developing and deploying stateâofâtheâart machine learning models for planning and prediction in AD/ADAS, along with their associated dataâprocessing pipelines and vehicle deployment. The ideal candidate has a deep passion for selfâdriving technology and its potential global impact. You will lead your team in advancing our core behavior machine learning models and accompanying pipelines. We are looking for an individual with domain expertise in machine learning, a comprehensive understanding of the model lifecycle, and experience developing tools and pipelines for behavior problems. Success in this role requires a candidate who thrives in a fastâpaced environment, is handsâon, and is eager to push the boundaries of our technology. Prior experience building and deploying realâworld autonomous driving products and collaborating with highly talented engineers is essential.

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, developing motion planning algorithms (e.g., trajectory optimization, sampling-based planning, model predictive control, and machine learning).
3+ years of experience managing engineering teams, with a focus on technical leadership, team development, and delivering high-impact projects in the automotive industry.
5+ years of experience with deep learning approaches such as supervised/unsupervised learning, transfer learning, multi-task learning, and/or deep reinforcement learning.
Extensive experience with learning-based planning approaches, including imitation learning, reinforcement learning, and state-of-the-art techniques for sequential modeling such as Transformer architectures.
5+ years of experience covering machine learning workflows: data sampling and curation, preprocessing, model training, ablation studies, evaluation, deployment, and inference optimization.
Passionate about self-driving car technology and its potential for humanity.
Strong communication skills, with the ability to convey concepts clearly and precisely.
Strong programming skills in Python.

Nice To Haves

Published research at topâtier conferences (NeurIPS, CoRL, CVPR, RSS, IROS, ICRA, and similar).
Proven track record of deploying ML models at scale in selfâdriving or related fields.
Familiarity with productionâlevel coding under timeâlimited task schedules.
Experience with robot motion planning (e.g., trajectory optimization, samplingâbased planning, model predictive control).
Experience with temporal data and/or sequential modeling.
Experience with selfâdriving challenges, including perception, prediction, planning, and simulation.

Responsibilities

Define the team's shortâterm and longâterm technical direction while collaborating on broader crossâfunctional strategic initiatives.
Initiate and influence crossâfunctional teams toward common development goals.
Enable and support other engineers on the team to be more effective through coaching, leading by example, providing highâquality code and designâdocument reviews, and delivering rigorous reports from ML experiments.
Be actively involved in dayâtoâday development and code review.
Collaborate with team members to design, develop, deploy, and evaluate stateâofâtheâart algorithms and capabilities for prediction and motion planning.
Use metrics to measure, validate, and improve performance through testing in simulation and on roads.
Design reusable software components as part of an integrated system.
Understand and fulfill software practices that produce maintainable code, including simulation, continuous integration, code review, HIL testing, and inâvehicle testing.
Be a champion of the scientific method and critical thinking to invent stateâofâtheâart deepâlearning solutions.
Work in a highâvelocity environment and employ agile development practices.
Collaborate closely with teams such as Perception, Simulation, Infrastructure, and Tooling to drive unified solutions.