Woven By Toyota2mo ago

Senior Production Machine Learning Engineer, Vehicle Perception

TokyoEmployeesenior

Data ScienceMachine Learning EngineerDataMachine LearningData & AI

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Overview

About Woven by Toyota 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 ScienceMachine Learning EngineerDataMachine LearningData & AI

About Woven by Toyota

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.

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TEAM

The Vehicle Perception team at Woven by Toyota tackles the core challenges of machine learning for 3D perception, sensor fusion, and computer vision in autonomous vehicles. Our work involves a variety of challenges, such as analyzing petabytes of multimodal driving data, solving optimization problems in computer vision, 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 onboard perception. We are looking for doers 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?

The team is looking for a skilled Production Machine Learning Engineer to help deploy advanced perception models to production-quality software modules that run reliably in an automotive ADAS/autonomy stack. You will have the chance to design and implement innovative machine learning models for our next-generation autonomous vehicle platform, influencing millions of Toyota production vehicles. We are looking for individuals who are excited to own the end-to-end ML lifecycle, from requirements, through training and verification, to safe, compliant deployment to mass production. Furthermore, we highly value candidates who exhibit a "giver" mindset, consistently seeking opportunities to assist their colleagues while maintaining a strong focus on delivering solutions to production.

Lead cross-functional efforts to establish and drive ML productionization processes enabling scalable and reliable deployment into mass production with rigorous safety standards

Optimize perception model inference performance for real-time deployment on automotive hardware using CUDA, TensorRT, mixed-precision inference, model compression, and real-time scheduling, while meeting strict latency and memory budgets

Design and implement observability and diagnostics for perception models, including runtime logging, health checks, fail-safe behaviors, and debuggability in the vehicle and in test environments

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

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

Work in a hybrid workspace, with the requirement to be present in our Nihonbashi (Japan) office three days per week

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

(3+years of) experience deploying machine learning models into production systems, preferably to mass-produced automotive or safety-critical platforms

Experience developing or deploying products in compliance with automotive production and development standards such as A-SPICE, PAS8800, ISO26262, or similar processes

(3+years of) experience with Python, any major deep learning framework, and software engineering best practices

(3+years of) experience with deep learning approaches such as supervised/unsupervised learning, transfer learning, multi-task learning, and/or deep reinforcement learning

(3+years of) experience covering machine learning workflows, data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, and inference optimization

Comfortable in writing C++ code to help integrate with our autonomous vehicle platform

Strong leadership skills to influence others and the team's technical strategy

Strong communication skills with the ability to communicate concepts clearly and precisely

Experience as ML feature owner in a safety-critical product (e.g., AD/ADAS, robotics, medical), with responsibility across design, implementation, verification, and monitored deployment in collaboration with systems, safety, and validation teams

Familiarity with production-level coding and deployment onto embedded platforms, optimizing for latency and hardware constraints

Experience designing and operating diagnostics and monitoring for ML systems in production, including defining KPIs, setting up logging and runtime analytics, and debugging issues that span data, model, and system boundaries

Published research at top-tier conferences (NeurIPs, CVPR and similar)

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

Experience in self-driving challenges (Perception, Prediction, Mapping, Localization, Planning, Simulation)