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Wayve is seeking a Staff Machine Learning Engineer based in Sunnyvale, California, to lead the Core Model Safety team. This role involves shaping a driving model that ensures safety and reliability in real-world conditions through research and technology transfer.
The ideal candidate will have over 5 years of experience in ML engineering, proficiency in Python and ML frameworks, and a track record of technical leadership. The position offers a competitive salary range of $336,400 to $370,300, along with a hybrid working policy.
As a Staff Machine Learning Engineer on Wayve’s Core Model Safety team in AV Core, you will help shape what our end‑to‑end driving model must understand to be safe and reliable in the real world – and turn that into trained capabilities, clear evidence, and adoption on the shared backbone across core and product engineering.
In order to set you up for success as a Staff Machine Learning Engineer at Wayve, we’re looking for the following skills and experience.
This is a full‑time role based in our office in Sunnyvale. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. The reasonably estimated salary for this role ranges from $336,400 to $370,300, plus a competitive equity package. Actual compensation is based on the candidate's skills, qualifications, and experience.
We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self‑driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply. 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.