Machine Learning Engineering Manager, App SW
Wayve, a leading developer of Embodied AI technology for autonomous vehicles, is seeking a Machine Learning Engineering Manager to lead their new Application Engineering team in the United States. This team will focus on localizing and advancing Wayve's autonomous driving technology to meet the unique challenges of the U.S. market. The role offers an opportunity to shape Wayve's autonomous vehicle capabilities in the U.S. from the ground up.
As the founding manager, you will build and lead a self-sufficient team of engineers specializing in robotics, machine learning, and systems integration. Your responsibilities will include developing autonomy features tailored to U.S. road infrastructure, cultural driving behaviors, and regulatory requirements. You will oversee the full development cycle, from identifying local autonomy needs to designing, implementing, testing, and deploying features into production. Collaboration with central autonomy teams and close work with OEM partners in the U.S. will be essential.
Ideal candidates will have a strong background in robotics and autonomy, with experience in building and deploying systems in real-world environments. Proven leadership skills, particularly in leading high-performing engineering teams in independent settings, are crucial. Comfort with ambiguity, the ability to define goals and deliver high-impact work with minimal supervision, and broad technical fluency across software engineering, machine learning, controls, and systems integration are required. Excellent communication skills and strong product sense are also essential.
The position is full-time, based in Sunnyvale, CA, or Detroit, MI (hybrid). The estimated annual salary ranges from $336,400 to $381,600, complemented by a competitive equity package. Actual compensation will be based on the candidate's skills, qualifications, and experience.
Wayve fosters a diverse and inclusive work environment, valuing contributions that drive impact. The company operates a hybrid working policy, combining time in offices and workshops to fuel innovation and culture, with flexibility for remote work. Core working hours are established to accommodate team schedules.