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.
=========================================================================
TEAM
The Behavior team at Woven by Toyota tackles Autonomy challenges for problems 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 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 Machine Learning Engineer to work in close collaboration with our ML teams to build efficient cloud and data curation pipelines, automated training, evaluation and release pipelines, as well as providing introspection tools in our data. You will have the chance to design and implement innovative machine learning pipelines, and help accelerate the release of models for our next-generation autonomous vehicle platform, influencing millions of Toyota customer vehicles. We are looking for individuals who are passionate about self-driving car technology and its potential impact on humanity.
RESPONSIBILITIES
Lead the development of foundational ML components to improve speed and ease of development of advanced machine learning models specifically tailored for autonomous vehicles utilizing deep learning and large-scale dataDeploy extensible, scalable and efficient ML data curation, training and evaluation cloud pipelinesAnalyze model performance metrics, model failure modes, statistical relevance of datasets, etc., to guide the overall ML engineering effortIntegrate modern technologies with rigorous safety standards while maintaining cost efficiencySignificantly contribute to the development of needed components for end-to-end ML training and deployment, from data strategy to optimization and validationOperate cross-functionally and serve a dual hat role in identifying opportunities to improve production models while also trailblazing and generalizing involved methods and toolings to empower othersBe a champion of the scientific method and critical thinking in inventing state-of-the-art deep learning solutionsWork in a high-velocity environment and employ agile development practicesWork in a hybrid workspace, with the requirement to be present in our Nihonbashi (Japan) office three days per week
MINIMUM QUALIFICATIONS
BSc / BEng (MS / PhD nice-to-have) in Machine Learning, Computer Science, Robotics or related quantitative fields, or equivalent industry experience3+ years of experience with Python, PyTorch/Tensorflow, and software engineering best practices3+ years of experience covering machine learning workflows, data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, and inference optimizationComfortable in writing C++ code to help integrate with our autonomous vehicle platformDeep understanding of runtime complexity, space complexity, distributed computing, and the application of these concepts in concrete, distributed ML training and evaluationExperience working with temporal data and/or sequential modelingStrong leadership skills to influence others and the team's technical strategyStrong communication skills with the ability to communicate concepts clearly and precisely
NICE TO HAVES
Experience with deep learning approaches such as supervised/unsupervised learning, transfer learning, multi-task learning, and/or deep reinforcement learning2+ years of experience with Apache Spark, Airflow, Flyte, Flink, Ray, or similar ML pipelines technologiesExperience deploying and tuning ML models onto custom edge hardware in robotics applicationsPreviously worked at, or in close collaboration with ML Research Engineers to deliver a solid software foundation that other ML Engineers can build onProven track record of deploying ML models at scale in self-driving or related fieldsFamiliarity with production-level coding in time-limited task schedulesExperience in self-driving, robotics, computer vision, or motion planning
