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Senior Machine Learning Engineer, Frameworks

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.

Average salary estimate

$185000 / YEARLY (est.)
min
max
$140000K
$230000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Machine Learning Engineer, Frameworks, Woven by Toyota

Join Woven by Toyota as a Senior Machine Learning Engineer, Frameworks and be at the forefront of transforming the future of mobility! At Woven, our mission is to deliver safe and human-centered automated driving solutions, leveraging cutting-edge technology at the intersection of AI, robotics, and advanced driving systems. As a Senior Machine Learning Engineer, you will collaborate with talented teams to design and implement sophisticated machine learning pipelines that enhance the capabilities of autonomous vehicles. You'll dive into the nitty-gritty of data analysis, model performance, and cloud-based environments while ensuring adherence to rigorous safety standards. Your role will involve developing foundational ML components, optimizing production models, and championing evidence-based approaches to achieve groundbreaking results. If you thrive in a dynamic environment and have a passion for self-driving technology, this opportunity to influence millions of Toyota vehicles is perfect for you. Join us in our mission to make mobility safer, smarter, and more enjoyable for everyone, all while working in a collaborative and innovative culture that marries the best of Silicon Valley with the craftsmanship of Japan.

Frequently Asked Questions (FAQs) for Senior Machine Learning Engineer, Frameworks Role at Woven by Toyota
What are the key responsibilities of a Senior Machine Learning Engineer at Woven by Toyota?

As a Senior Machine Learning Engineer at Woven by Toyota, you will be responsible for developing ML components tailored for autonomous vehicles, deploying scalable cloud pipelines for data curation, and analyzing model performance metrics to guide your engineering efforts. A significant part of your role will involve cross-functional collaboration to improve production models, along with trailblazing methods and tools that empower fellow engineers in their work.

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What qualifications do I need to become a Senior Machine Learning Engineer at Woven by Toyota?

To qualify for the Senior Machine Learning Engineer position at Woven by Toyota, candidates should possess a BSc or BEng in Machine Learning or related fields, along with 3+ years of experience with Python, ML frameworks like PyTorch or TensorFlow, and a solid grasp of software engineering practices. Additionally, familiarity with C++, distributed computing, and machine learning workflows will be valuable. Advanced degrees and experience with robotics or self-driving technology are considered a plus.

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What programming languages and tools are essential for a Senior Machine Learning Engineer at Woven by Toyota?

For the Senior Machine Learning Engineer role at Woven by Toyota, proficiency in Python and common ML libraries such as PyTorch or TensorFlow is essential. Experience with C++ for integrating with the autonomous vehicle platform is also required. Familiarity with tools and technologies like Apache Spark, Airflow, and cloud-based ML deployment environments will help you excel in this position.

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How does Woven by Toyota support employee work-life balance?

Woven by Toyota believes in creating a modern work environment that supports a healthy work-life balance. As a Senior Machine Learning Engineer, you can expect a flexible vacation policy, excellent health and wellness benefits, and family planning support, allowing you to focus on doing meaningful work while nurturing your personal life.

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What opportunities for career growth does Woven by Toyota provide for Senior Machine Learning Engineers?

At Woven by Toyota, Senior Machine Learning Engineers are encouraged to explore opportunities for career advancement through professional development, cross-functional collaboration, and working on innovative projects impacting the autonomous vehicle industry. Your contributions will not only enhance your career prospects but also shape the future of mobility.

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Common Interview Questions for Senior Machine Learning Engineer, Frameworks
Can you explain your experience with machine learning frameworks for autonomous vehicles?

When preparing for this question, highlight specific projects where you've used machine learning frameworks like TensorFlow or PyTorch to build models for autonomous systems. Discuss any challenges you faced and how you overcame them, emphasizing your understanding of model training and evaluation.

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What strategies do you use to ensure model performance and reliability in machine learning?

Detail the steps you take to validate model performance, including creating ablation studies, analyzing failure modes, and utilizing robust evaluation metrics. Emphasize your analytical skills and your commitment to following the scientific method to enhance reliability in your machine learning projects.

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How do you approach cross-functional teamwork in a machine learning environment?

Share your experiences collaborating with different teams, such as data engineers or product managers, to align on project goals. Explain how effective communication and a willingness to assist others play a vital role in achieving shared success in your machine learning initiatives.

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Describe a time when you had to analyze large datasets for your machine learning projects.

Focus on a particular project where you faced heavy data workloads, detailing how you used data curation and sampling techniques to optimize your model building process. Discuss any tools you utilized and the final impact on the project outcome.

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What role does distributed computing play in your machine learning workflows?

Explain how you leverage distributed computing to optimize training times and manage large-scale datasets. Define specific tools and frameworks you’ve used and discuss how they benefited your projects, particularly regarding scalability and performance.

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How do you ensure your machine learning pipelines are efficient and cost-effective?

Describe your methodology for optimizing machine learning pipelines by balancing resource use with performance. Mention any specific techniques or tools you have used to improve cost efficiency without sacrificing model accuracy.

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What is your experience with deploying machine learning models in a production environment?

Share your experience deploying models, discussing the steps you took to maintain model performance post-deployment. Highlight any challenges you faced and how you ensured the models continued to operate effectively in a live environment.

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How do you continue to learn about advancements in machine learning and AI?

Discuss the resources that keep you updated on AI advancements, like research papers, online courses, or conferences. Highlight your commitment to continuously improving your knowledge and skills to stay relevant in this fast-evolving field.

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Can you discuss your experience with safety standards in machine learning for autonomous vehicles?

Detail your understanding of safety protocols and regulations related to automated driving systems. Share experiences where you ensured compliance in your projects, underscoring the importance of safety in your machine learning practices.

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What approaches do you take to implement innovative solutions in machine learning?

Talk about your strategy for fostering creativity and innovation in your work. Give examples of when you introduced new methodologies or technologies that improved project outcomes, highlighting your proactive problem-solving attitude.

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Software-Defined Vehicle. Arene is a modern software platform developed to support the creation, deployment and continuous improvement of software-defined vehicles. The Arene Vehicle Platform consists of build tools and on-vehicle software, and th...

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Full-time, hybrid
DATE POSTED
January 28, 2025

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