Senior Machine Learning Engineer, Arene AI – Edge

Woven Planet

  • Full Time

Woven Planet Group (Woven Planet) represents a carefully curated blend of expertise and resources dedicated to bringing the vision of “Mobility to Love, Safety to Live” to life. Through innovations and investments in automated driving, robotics, smart cities, and more, we are transforming how humankind lives, works, and moves. We exist to design, build, and deliver secure, connected, and sustainable mobility solutions that benefit all people worldwide. Founded in 2018 as Toyota Research Institute – Advanced Development (TRI-AD), Woven Planet is composed of four complementary companies: Woven Planet Holdings, Woven Core, Woven Alpha, and Woven Capital.

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Arene AI is on a mission to simplify vehicle software development and increase developer agility by creating tools and processes which enable novel uses of vehicles without compromising safety. Arene AI is a function that supports Arene, by building a new and exciting machine learning platform for all. As a member, you will have the opportunity to work with business partners, leadership and other passionate engineers, throughout Woven Planet, the Toyota Group and many vendors. We are agile using best practices in all developer disciplines to deliver the best in quality and value.

As a Senior ML Engineer in the Machine Learning (ML) Tools team, you will work alongside research scientists and engineers not only within Woven Planet but throughout the Toyota Group and its vendors. You will be responsible for designing and implementing ML algorithms and computer vision (CV) applications for production vehicles. We are looking for engineers who are passionate about building tools and frameworks to enable cutting-edge ML / CV solutions for real-world autonomous driving problems.




  • Design and implement ML models and algorithms for real-world autonomous driving problems.
  • Build workflows for ML / CV applications from the cloud to edge devices.
  • Lead safe ML model / CV applications and frameworks development according to ISO standards.
  • Collaborate with other engineers and scientists to develop high-performance frameworks and tools
  • Design, communicate, and build new features to meet the needs of customers both inside and outside of Woven Planet



  • 5+ years ML experience in training/evaluation of deep learning models and development of robust and scalable ML products or tools
  • ML experiences which involve ML deployment tools and frameworks for edge devices.
  • Strong Python skills with strong ability to write high quality, unit-testable code
  • Strong communication skills, team player and a good listener as well as customer focus with a “Can-Do” attitude
  • Experience with SCM tools and processes: Git, Continuous Integration, Code Reviews



  • Strong knowledge with ML application domains such as federated learning, neural architecture search, active learning, domain adaptation, image synthesis, and self-supervised learning.
  • Experience with cloud tools and processes: AWS, GCP
  • Experienced to build a MLOps pipeline.
  • ISO26262 and ISO/PAS 21448 knowledge/work experience is a plus
  • Experience in contributing to or maintaining open-source especially in machine learning software is a plus


    If you are currently located outside of Japan, don’t worry, we’ll set an interview over Google Hangout Meet or Skype.
    ・Competitive Salary – Based on skills and experience
    ・Work Hours – Flexible working time with NO core-hours
    ・Paid Holiday – 20 days per year (prorated)
    ・Sick Leave – 6 days per year (prorated)
    ・Holiday – Sat & Sun, Japanese National Holidays, and other days defined by the company
    ・Japanese Social Security – all applicable (Health Insurance, Pension, Workers’ Comp, and Unemployment Insurance, Long-term care insurance)
    ・In-house Training Program (software study/language study)
    By submitting your application you agree to the following terms:
    ・We are an equal opportunity employer and value diversity.
    ・We pledge that any information we receive from candidates will be used ONLY for the purpose of hiring assessment.