Machine Learning Engineer

Woven by Toyota
United States
20 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Compensation
$140,000.0 - $230,000.0
Working hours
Regular working hours
Job source

Tech stack

Computer Vision C++ (Programming Language) Python (Programming Language) Machine Learning Motion Planning Software Construction Reinforcement Learning Transfer Learning Deep Learning Data Strategy Low Latency Machine Learning Operations
+3 more
Multiaccess Edge Computing Data Pipelines Unsupervised Learning

Job description

  • 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.

Requirements

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 β€œgiver” mindset, consistently seeking opportunities to assist their colleagues while maintaining a strong focus on delivering solutions to production., * 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).

Benefits & conditions

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., 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

About the company

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 β€œmobility” 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 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.

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Good distractions

Talks and stories from around this role β€” technically off-topic, practically not.

1:33 min

Summary of machine learning capabilities and engineering opportunities

Jan Zawadzki Β· LIVE

5:48 min

Balancing delivery latency with stream reliability and scale

Phil Cluff Β· LIVE

1:25 min

Distinguishing artificial intelligence from deep learning

Sam Witteveen Β· Coffee With Developers

1:15 min

Three pillars of the data and AI strategy

Dominik Schneider Dominik Schneider Β· World Congress 2025

3:37 min

Transitioning automated driving to neural networks and model-based perception

Katrin Lehmann Katrin Lehmann +1 Β· World Congress 2025

3:37 min

Accessing API documentation and testing remote driving latency

Alexandru Ciinaru Alexandru Ciinaru +3 Β· World Congress 2025

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