Woven by Toyota
Staff Machine Learning Engineer, Behavior Planning & Prediction
Woven by Toyota, Ann Arbor, Michigan, us, 48113
Staff Machine Learning Engineer, Behavior Planning & Prediction
Join the
Staff Machine Learning Engineer, Behavior Planning & Prediction
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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. 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. WHO ARE WE LOOKING FOR? The Behavior team is looking for a skilled Machine Learning Engineer to help advance cutting-edge machine learning systems for prediction and motion planning in autonomous driving. Responsibilities
Define the technical roadmap for the team towards short and long term development. Initiate and Influence cross-functional teams towards common development goals. Initiate high risk, high rewards projects towards overall business goals. Guide the design and development towards 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. Own development of new ML models end-to-end from data strategy, initial development, optimization, production platform validation, and fine tuning based on metrics and on road performance. Lead large, multi-person projects and significantly influence the overall Motion Planning architecture and technical direction. Enable and help other engineers on the team to be more effective through coaching and leading by example and by providing high-quality code and design document reviews and delivering rigorous reports from ML experiments. Significantly contribute to development of needed 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. Minimum Qualifications
MS or PhD in Machine Learning, Computer Science, Robotics or related quantitative fields, or equivalent industry experience. 5+ years of experience with Python, any major deep learning framework, and software engineering best practices Comfortable in writing C++ code to help integrate with our autonomous vehicle platform. 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 like imitation learning, reinforcement learning and state-of-the-art techniques for sequential modeling like Transformer architectures. 5+ years of experience covering machine learning workflows, data sampling and curation, pre-processing, 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 communicate concepts clearly and precisely. NICE TO HAVES
Published research at top-tier conferences (NeurIPs, RSS, IROS, ICRA, and similar). 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 with temporal data and/or sequential modeling. Experience in self-driving challenges (Perception, Prediction, Planning, Simulation). For positions based in Palo Alto, CA, the base pay for this position ranges from $161,000- $264,500 a year. What We Offer
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.
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Join the
Staff Machine Learning Engineer, Behavior Planning & Prediction
role at
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. 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. WHO ARE WE LOOKING FOR? The Behavior team is looking for a skilled Machine Learning Engineer to help advance cutting-edge machine learning systems for prediction and motion planning in autonomous driving. Responsibilities
Define the technical roadmap for the team towards short and long term development. Initiate and Influence cross-functional teams towards common development goals. Initiate high risk, high rewards projects towards overall business goals. Guide the design and development towards 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. Own development of new ML models end-to-end from data strategy, initial development, optimization, production platform validation, and fine tuning based on metrics and on road performance. Lead large, multi-person projects and significantly influence the overall Motion Planning architecture and technical direction. Enable and help other engineers on the team to be more effective through coaching and leading by example and by providing high-quality code and design document reviews and delivering rigorous reports from ML experiments. Significantly contribute to development of needed 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. Minimum Qualifications
MS or PhD in Machine Learning, Computer Science, Robotics or related quantitative fields, or equivalent industry experience. 5+ years of experience with Python, any major deep learning framework, and software engineering best practices Comfortable in writing C++ code to help integrate with our autonomous vehicle platform. 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 like imitation learning, reinforcement learning and state-of-the-art techniques for sequential modeling like Transformer architectures. 5+ years of experience covering machine learning workflows, data sampling and curation, pre-processing, 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 communicate concepts clearly and precisely. NICE TO HAVES
Published research at top-tier conferences (NeurIPs, RSS, IROS, ICRA, and similar). 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 with temporal data and/or sequential modeling. Experience in self-driving challenges (Perception, Prediction, Planning, Simulation). For positions based in Palo Alto, CA, the base pay for this position ranges from $161,000- $264,500 a year. What We Offer
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.
#J-18808-Ljbffr