AI/ML Quality Engineer

Tokyo
Technology Shared Services – Global Safety and Quality /
Employee /
Hybrid
About Woven by Toyota
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 “mobility” 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.

=========================================================================

TEAM
We are seeking an experienced AI/ML Quality Engineer to join the Global Safety and Quality team responsible for ensuring that technology deliveries from all Woven by Toyota lines of business meet the safety, security, and quality requirements defined by regulations, international standards and internal Toyota rules. This role serves as the second line of defense AI quality expert, ensuring that industry best practices, rules and standards are efficiently integrated into the development of all AI technology. The candidate will work closely with requirements, architecture, V&V, tooling, product integrity and many other teams within all Woven by Toyota lines of business to guide the teams in developing high quality, safety and security AI technology.     

This role is critical for ensuring our AI-based solutions are seamlessly integrated into vehicles and delivered to our customers, as well as meet the highest quality standards.

RESPONSIBILITIES

    • Regularly review and improve Woven by Toyota internal engineering standards with regards to the new standards and regulations that are being released for the AI technology, and align with stakeholders from in/outside of the company.
    • Assist engineering teams in defining and implementing tailored engineering processes with the focus on AI technology development.
    • Support product integrity teams in defining and managing AI technology quality and safety acceptance metrics and criteria.
    • Participate in the identification of risks, hazards and potential failures of the products that contain AI technology, acting as a facilitator and mentor during these activities.
    • Guide engineering teams through the evaluation and qualification of the SW tools that are used for the AI technology development or contain AI “under the hood”.
    • Perform review and assessments of the work products related to the AI technology and created by the engineering teams, highlighting any gaps and managing findings resolution plans.
    • Participate in engineering teams audit sessions to help identify any process deployment and execution gaps related to the AI engineering activities.
    • Own competency management plans for engineers and managers, creating, maintaining and executing them, including active contribution to the Woven by Toyota training programs.
    • Steer data management frameworks safety and quality across multiple lines of business, assuring data integrity, quality and safety are assured.
    • Promote the safety and quality culture across the company together with the Global Safety and Quality team.

MINIMUM QUALIFICATIONS

    • Minimum 8-10 years experience in the automotive or AV industry for mass production(ideally with the focus on software safety or quality).
    • Bachelor’s degree in Computer Science, Electrical Engineering, Data Science, or Software Engineering.
    • Strong knowledge of SW engineering processes and tools (i.e., github/gitlab, unit test frameworks, 
    • Strong understanding of the AI technologies used in the automotive industry (e.g., CNNs, RNNs, Transformer-based architectures) and at least 2 years of practical experience working with such technologies.
    • ML engineering experience with pytorch and/or tf+keras (C++ and/or Python).
    • Understanding of the C++ syntax and ability to read and analyse the codebase.
    • Knowledge of how data build tools and data pipelines work (dbt, Snowflake).
    • Business level English and Japanese.

NICE TO HAVES

    • Master’s or PhD in Artificial Intelligence, Machine Learning, Robotics, or Applied Statistics.
    • Practical experience with ISO 26262-6 and ISO 26262-8 C11.
    • Experience implementing ISO 21448.
    • Knowledge of SQuaRE series of standards (ISO 250xx).
    • Familiarity and/or experience with STPA/STAMP.
    • Knowledge of simulator technologies.
    • Experience of Japanese automotive OEM/supplier cultures
=========================================================================
Important Points
・All interviews will be arranged via Google Meet, unless otherwise stated.
・The same job descriptions are available in both English and Japanese; therefore, we kindly ask that you apply to only one version.
・We kindly request that you submit your resume in English, if possible. However, Japanese resumes are also acceptable. Please note that, depending on the English proficiency requirements of the role, we may request an English version of your resume later in the process.

WHAT WE OFFER
・Competitive Salary - Based on experience
・Work Hours - Flexible working time
・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 our company
・Japanese Social Insurance - Health Insurance, Pension, Workers’ Comp, and Unemployment Insurance, Long-term care insurance
・Housing Allowance
・Retirement Benefits
・Rental Cars Support
・In-house Training Program (software study/language study)

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.