🕒 7 days ago
Train and ship computer vision and 3D perception models for ADAS, owning work across data, evaluation, and iteration to improve real-world driving performance under production constraints.
Senior Machine Learning Engineer, Vehicle Perception
📅 Aug 13
Machine LearningComputer Vision3D PerceptionSensor Fusion
📜 Description
- Design and develop perception foundation models that unify sensor data for scalable 3D scene understanding.
- Deploy scalable, efficient machine learning models on autonomous vehicle platforms.
- Build components across end-to-end ML training and deployment, from data strategy through optimization and validation.
- Develop state-of-the-art deep learning solutions using scientific methods and critical thinking.
- Collaborate with Perception, Motion Planning, Simulation, Infrastructure, and Tooling teams on unified solutions.
- Apply agile development practices in a high-velocity environment.
🛠️ Requirements
- MS or PhD in Machine Learning, Computer Vision, Robotics or related quantitative fields, or equivalent industry experience.
- 3+ years of experience with Python, any major deep learning framework (PyTorch preferred), 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.
- Experience working with large-scale foundation models, including pretraining, multimodal architectures, self-supervised learning approaches.
- Deep understanding of runtime complexity, distributed/cloud ML infrastructure, data pipeline architecture,resource-aware 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.
- Published research at top-tier conferences (NeurIPs, CVPR and similar).
✨ Benefits
- Health coverage
- Wellness coverage
- Dental coverage
- Vision coverage
- 401(k) program
- Flexible vacation policy
- Family planning and care benefits
- Short-term and long-term incentives
Full job description
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.
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.
The base pay for this position ranges from $140,000 - $230,000 a year.
Your base salary is one part of your total compensation. We offer a base salary, short term and long term incentives, and a comprehensive benefits package. The total compensation offered to an employee will be dependent upon the individual's skills, experience, qualifications, location, and level.
WHAT WE OFFER
We are committed to creating a modern work environment that supports our employees and their loved ones. We offer many options of the best programs to allow you to do your most meaningful work and to help you shape the future of mobility.
・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. Please see our privacy notice for more details.
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 Machine Learning Engineer to help advance a cutting-edge machine learning system for perception foundation models leveraging large-scale multimodal sensor data. 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 passionate about self-driving car technology and its potential impact on humanity. 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.
RESPONSIBILITIES
MINIMUM QUALIFICATIONS
MS or PhD in Machine Learning, Computer Vision, Robotics or related quantitative fields, or equivalent industry experience.
3+ years of experience with Python, any major deep learning framework (PyTorch preferred), 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.
Experience working with large-scale foundation models, including pretraining, multimodal architectures, self-supervised learning approaches.
Deep understanding of runtime complexity, distributed/cloud ML infrastructure, data pipeline architecture,resource-aware 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.
NICE TO HAVES
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 with offboard, auto-labeling, or "data-engine" pipelines, including mining, curation, active learning, and ground-truth-free evaluation for large-scale datasets.
Hands-on experience with vision-language models (VLMs), world models, video prediction, or latent dynamics models for autonomous systems or robotics.
Experience leveraging foundation models across multiple platforms and sensor setups, including distilling larger models into efficient real-time variants.
Familiarity with production-level coding and deployment onto embedded platforms, optimizing for latency and hardware constraints.
Experience in self-driving challenges (Perception, Prediction, Mapping, Localization, Planning, Simulation).
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