Senior/Staff Online Mapping Machine Learning Engineer Full-time

Woven by Toyota is the mobility technology subsidiary of Toyota Motor Corporation. Our mission is to deliver safe, intelligent, human-centered mobility for all. Through our Arene mobility software platform, safety-first automated driving technology and Toyota Woven City – our test course for advanced mobility – we’re bringing greater freedom, safety and happiness to people and society.

Our unique global culture weaves modern Silicon Valley innovation and time-tested Japanese quality craftsmanship. We leverage these complementary strengths to amplify the capabilities of drivers, foster happiness, and elevate well-being.

AD/ADAS, TEAM

At Woven by Toyota, we work on a diverse set of problems ranging from solving optimization problems in 3D geometric computer vision, to minimizing latency on hardware accelerators, designing novel neural network architectures and applying and advancing the state-of-the-art of machine learning (ML) for perception, prediction, and motion planning. We are looking for doers and creative problem solvers to join us in improving mobility for everyone with self-driving technology. You will be interacting on a daily basis with other software and hardware engineers and researchers to tackle some of the most challenging problems in AI, robotics, and computer vision.

WHO ARE WE LOOKING FOR?

The AD/ADAS team is seeking a skilled Machine Learning engineer to help develop a state-of-the-art online mapping system for autonomous driving. Unlike traditional approaches that rely on high-definition (HD) maps to provide road geometry, speed limits, and other essential data for autonomous vehicle operation, our system uses real-time machine learning models to infer this information directly from perception data.

As a Machine Learning engineer, your role will be to drive innovation and advance the state of the art in online map recognition, while considering constraints such as memory, computing power, and sensor capabilities. You will collaborate with other Machine Learning engineers to train, validate, and deploy new models, ensuring seamless integration with the broader autonomy stack. The system will be continuously tested on both prototype and near-production autonomous vehicles, with a concrete goal of deploying this technology in millions of Toyota vehicles in the near future. You will also closely collaborate with our autolabeling team that generates ground truth data to facilitate reuse of ML models and principles across the online and offline domain.

We recognize the unique capabilities each team member brings, and encourage applicants to reach out even if they do not match all of the characteristics described below.

RESPONSIBILITIES

• Contribute to ML model R&D by prototyping, validating and iterating on existing and new model architectures towards an online mapping system.
• Own end-to-end development of new ML models,from data strategy, initial development, optimization, production platform validation, and fine tuning based on metrics and on-road performance.
• Lead multi-person projects and influence the overall AD/ADAS online mapping architecture and technical direction.
• Enable and help other engineers on the team to be more effective through coaching and leading by example when it comes to writing high-quality code, providing high-quality code and design document reviews and delivering rigorous reports from ML experiments.
• Work in a high-velocity environment and employ agile development practices.
• Team player and “get things done” mentality
• Collaborate closely with stakeholders in downstream customer teams to define interfaces and requirements for the Perception stack.
• Closely collaborate with Perception subteams to develop end-to-end solutions.

MINIMUM QUALIFICATIONS

• MS or higher degree in CS/CE/EE, or equivalent industry experience.
• 3+ years of experience with ML frameworks such as PyTorch, Caffee, or Tensorflow
• 3+ years of experience in machine learning workflows: data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, inference optimization.
• Extensive experience with machine learning and classification problems.
• Strong programming skills in Python or C++.
• Passionate about applying ML methodology to advance self driving technology.
• Strong communication skills and ability to communicate concepts clearly and precisely.
• Experience in production-level software development best practices.

NICE TO HAVES

• Experience in developing vision-first Perception and Mapping ML models
• Hands-on experience with building a perception stack for autonomous systems.
• Experience with commercially available automotive maps.
• Experience in runtime optimization for mission-critical systems on Linux and UNIX-like real-time operating systems.
• Experience with CUDA or OpenCL.
• Experience with automotive grade edge-compute platforms.
• Experience with building safety-critical software architectures.

Senior Online Mapping Machine Learning Engineer: The base pay for this position ranges from $140,000- $230,000 a year

Staff Online Mapping Machine Learning Engineer:: The base pay for this position ranges from $161,000- $264,500 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.