Machine Learning Engineer - Hybrid Working

New Yesterday

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. 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 intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving.
We value diversity, embrace new perspectives, and foster an inclusive work environment; This is a high-impact opportunity to shape how Wayve evaluates its foundation models for embodied AI. You'll lead the development of our offline evaluation suite—designing robust, interpretable metrics for tasks ranging from action and perception to language-grounded reasoning. Working closely with science, datasets, and infra teams, you'll also drive human annotation efforts to ensure high-quality ground truth data. Build and scale offline evaluation pipelines for embodied AI models
Design and implement benchmarks and metrics across vision, language, and driving tasks
Lead and coordinate human annotation workflows, including quality assurance and task design
Analyze offline metrics and correlate them with online performance to inform deployment readiness
In order to set you up for success as a Senior Machine Learning Engineer – Evaluation at Wayve, we’re looking for the following skills and experience:
~~5+ years of relevant industry, including experience designing and implementing offline evaluation pipelines for ML models (vision, multimodal, or embodied AI)
~ Strong software engineering skills, including Python, data processing, and ML tooling
~ Experience with foundation models (LLMs or VLMs) and their evaluation
~ Background in autonomous systems, robotics, or embodied AI domains
~ Attractive compensation with salary and equity
Bespoke learning and development opportunities
Relocation support with visa sponsorship
Flexible working hours - we trust you to do your job well, at times that suit you and your time
Benefits such as an onsite chef, workplace nursery scheme, private health insurance, therapy, daily yoga, onsite bar, large social budgets, unlimited L&D requests, enhanced parental leave, and more!
This is a full-time role based in our office in London. 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.
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.
We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.
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Learn more about how we handle your data for recruiting purposes in our privacy notice: * Do you have multiple years of machine learning algorithm development experience? * Are you comfortable commuting into one of our offices 2-3 days a week? * For candidates who complete the questionnaire, their data will be anonymised and used only in the aggregate to inform our attraction strategy. Wayve is an equal opportunity employer and this data will be used for opportunity monitoring purposes.
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Location:
Wandsworth, Greater London
Job Type:
FullTime

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