Senior Machine Learning Engineer, Vehicle Perception

Woven by Toyota; Palo Alto (CA); Hybrid; USD 140,000 - 230,000; Full time

Benefits offered by this job

Excellent health, wellness, dental and

401k program

Flexible vacation policy

Family planning and care benefits

Job summary

Woven by Toyota seeks a skilled Machine Learning Engineer to advance perception foundation models for autonomous vehicles, leveraging large-scale multimodal data. You will design and deploy models that drive Toyota's next generation platform, with emphasis on safety, performance, and production readiness.

Join our Vehicle Perception Team in a hybrid environment, collaborating across Perception, Motion Planning, Simulation, and Infrastructure to ship solutions that scale across vehicles worldwide.

Qualifications

• MS or PhD in Machine Learning, Computer Vision, Robotics, or related field, or equivalent industry experience.
• 3+ years with Python, DL frameworks, and software engineering best practices.
• 3+ years with DL approaches and ML workflows from data curation to deployment.
• Experience with large-scale foundation models and multimodal architectures.
• Strong knowledge of runtime, cloud infrastructure, and data pipelines.
• Comfortable writing C++ code to integrate with AV platform.
• Strong leadership and communication skills.

Responsibilities

• Lead design and development of perception foundation models for autonomous vehicles.
• Deploy scalable ML models on the AV platform.
• Integrate technologies with safety standards while optimizing cost.
• Contribute to end-to-end ML training and deployment components.
• Promote the scientific method and robust deep learning solutions.
• Collaborate with Perception, Motion Planning, Simulation, and Infrastructure teams.
• Work in a hybrid model with three days per week in Palo Alto or other offices.

Skills

Python

Deep Learning Frameworks

ML Workflows

Foundation Models

C++

Leadership

Communication

Education

MS/PhD in ML/CS/Robotics

Tools

TensorFlow

PyTorch

CUDA

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.

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

• Senior Lead the design and development of perception foundation models for autonomous vehicles, unifying diverse sensor data for scalable 3D scene understanding.
• Deploy scalable and efficient ML models on our autonomous vehicle platform.
• Integrate modern technologies with rigorous safety standards while maintaining cost efficiency.
• 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 in inventing 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, 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), Palo Alto (California), or Ann Arbor (Michigan) offices three days per week.

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, 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.
• Hands‑on experience with 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).

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.