Machine Learning Manager, App SW
WayveJapanPosted 30 March 2026
Tech Stack
Job Description
At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law.
About us
Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems.
Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.
In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future.
At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact.
Make Wayve the experience that defines your career!
The Role
We're looking for an exceptional technical leader to spearhead our new Japan-based Application Engineer team, a self-sufficient and high-impact group focused on localising and advancing our autonomous driving technology for the Japanese market. This is a unique opportunity to shape Wayve’s AV capabilities in Japan from the ground up.
Here you’ll lead a small but mighty team of engineers working across robotics, machine learning, and systems integration. You'll drive development of autonomy features tailored for Japan’s road infrastructure, cultural driving behaviours, and regulatory landscape, ensuring our AV stack performs safely and effectively in this highly distinctive environment.
Given the geographical and time zone distance from our London HQ, your team will operate with significant autonomy. We’re looking for someone who thrives in self-directed, startup-like conditions, capable of setting a vision, executing fast, and making robust decisions independently — while staying aligned with global engineering efforts.
This role requires breadth: strong experience across AV systems, including robotics and autonomy, is essential. If you also bring deep expertise in machine learning, that's a major plus.
Key Responsibilities:
Build and lead a self-sufficient AV development team in Japan, hiring and mentoring top talent across robotics and ML.
Deliver autonomy capabilities tailored to Japanese road conditions and driving norms, in close collaboration with central Autonomy teams.
Act as the primary technical and operational bridge between the Japan office and HQ, aligning roadmaps and communicating local insights.
Drive full-cycle development: from identifying local autonomy needs, to designing, implementing, testing, and deploying features into production.
Ensure the team upholds Wayve’s high engineering standards, while operating with agility and independence.
Work closely with OEM partners in Japan — representing Wayve’s autonomy team in technical discussions, capturing product requirements, and shaping joint development plans.
Establish close working relationships with our product and vehicle operations teams in Japan.
About You
In order to set you up for success as a ML Engineering Manager at Wayve, we’re looking for the following skills and experience.
Essential
A strong background in robotics and autonomy, with experience building and deploying systems that operate in real-world environments.
Demonstrated ability to lead and grow high-performing engineering te ... (truncated, view full listing at source)
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