Senior Machine Learning Software Engineer, Frameworks 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.

TEAM

At Woven by Toyota, we tackle Autonomy challenges at the intersection of AI, Robotics, and Advanced Driving. 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 Perception, Prediction, and Motion Planning. 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 work in close collaboration with our ML teams to build efficient cloud and data curation pipelines, automated training, evaluation and release pipelines, as well as providing introspection tools in our data. You will have the chance to design and implement innovative machine learning pipelines, and help accelerate the release of models for our next-generation autonomous vehicle platform, influencing millions of Toyota customer vehicles. We are looking for individuals who are passionate about self-driving car technology and its potential impact on humanity.

RESPONSIBILITIES

• Develop foundational ML components to improve speed and ease of development of advanced machine learning models specifically tailored for autonomous vehicles utilizing deep learning and large-scale data.
• Deploy extensible, scalable and efficient ML data curation, training and evaluation cloud pipelines.
• Analyze model performance metrics, model failure modes, statistical relevance of datasets, etc. to guide the overall ML engineering effort.
• Integrate modern technologies with rigorous safety standards while maintaining cost efficiency.
• Significantly contribute to the development of needed components for end-to-end ML training and deployment, from data strategy to optimization and validation.
• Operate cross-functionally and serve a dual hat role in identifying opportunities to improve production models while also trailblazing and generalizing involved methods and toolings to empower others.
• 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.
• Exhibit a “Giver” mindset, proactively asking, “What can I do for you?” to facilitate production development processes while maintaining a “get things done” mentality.
• 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

• BSc / BEng (MS / PhD nice-to-have) in Machine Learning, Computer Science, Robotics or related quantitative fields, or equivalent industry experience.
• 3+ years of experience with Python, PyTorch/Tensorflow, and software engineering best practices.
• 2+ years of experience covering machine learning workflows, data sampling and curation, pre-processing, model training, ablation studies, evaluation, deployment, and inference optimization.
• Comfortable in writing C++ code to help integrate with our autonomous vehicle platform.
• Deep understanding of runtime complexity, space complexity, distributed computing, and the application of these concepts in concrete, distributed ML training and evaluation.
• Experience working with temporal data and/or sequential modeling.
• Strong communication skills with the ability to communicate concepts clearly and precisely.

NICE TO HAVES

• Experience with deep learning approaches such as supervised/unsupervised learning, transfer learning, multi-task learning, and/or deep reinforcement learning.
• 2+ years of experience with Apache Spark, Airflow, Flyte, Flink, Ray, or similar ML pipelines technologies.
• Experience deploying and tuning ML models onto custom edge hardware in robotics applications.
• Previously worked at, or in close collaboration with ML Research Engineers to deliver a solid software foundation that other ML Engineers can build on.
• 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 in self-driving, robotics, computer vision, or motion planning.

For California: 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.