Engineering Manager - Autonomous Driving Forensics

Wayve
London
1 month ago
Create job alert

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.

At Wayve, 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 RoleAs theEngineering Manager - Autonomous Driving Forensics Engineer, you will lead a cross-functional team focused on identifying and resolving systemic issues in autonomous vehicle (AV) performance. Leveraging your expertise in robotics and AI, you will provide actionable insights that drive improvements in our end-to-end AV stack, empowering development teams to deliver world-class performance.

You will work closely with software engineers, roboticists, platform developers, and operational teams to investigate AV behaviour in real-world and simulated environments. Your leadership will guide the development of innovative solutions, ensuring issues are resolved efficiently and effectively.

Key responsibilities:

Lead cross-functional teams to identify, analyse, and resolve complex performance issues in AV systems. Apply your robotics and AI expertise to investigate systemic issues across the AV stack. Design and oversee experiments to test hypotheses and improve system performance. Leverage video, simulation, and telemetry data to identify trends and root causes. Communicate findings and strategies to technical and non-technical stakeholders. Drive statistical rigour and best practices in performance analysis and experimentation. Collaborate with developers to implement solutions and track performance improvements.

About You

Essential:

5+ years of experience working with complex robotics or AI systems, including leadership roles. Proven ability to design experiments for real-world robotic systems and analyse their results. Exceptional problem-solving and critical thinking skills to address complex technical challenges. Strong communication skills for engaging with both technical and non-technical audiences. Experience with statistical scripting and data analysis tools (e.g., Python with pandas, sklearn, scipy). Proficiency in remote Linux environments and hands-on debugging. Demonstrated ability to influence organisational direction through actionable insights.

Desirable:

Hands-on experience with machine learning frameworks (e.g., PyTorch). Passion for transitioning research ideas into production-grade solutions. Strong advocate for statistical rigour and experimental best practices. Experience in fast-paced tech environments or startups. Expertise in Python and data science workflows.

This is a full-time role based in our office in Sunnyvale or 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. We operate core working hours so you can determine the schedule that works best for you and your team.

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.

For more information visit Careers at Wayve. 

To learn more about what drives us, visit Values at Wayve 

DISCLAIMER: 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.

Related Jobs

View all jobs

Engineering Manager

Engineering Manager

Engineering Manager - Autonomous Driving Forensics

Data Engineering Manager

Data Engineering Manager

Senior Engineering Manager - HVDC Control & Protection

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

UK Visa & Work Permits Explained: Your Essential Guide for International Machine Learning Professionals

Machine learning continues to redefine the global tech landscape, enabling transformative breakthroughs in sectors as diverse as healthcare, finance, retail, gaming, and autonomous vehicles. The United Kingdom has emerged as a hotbed for machine learning (ML) research and development, thanks to its world-class universities, well-funded start-up scene, and a broad base of established corporations adopting AI-driven solutions. For international professionals specialising in ML, the UK’s growing demand and favourable ecosystem offer exciting opportunities to innovate and advance your career. Yet, before you can join this dynamic environment, you’ll need to secure the correct work visa or permit. This article offers a comprehensive breakdown of the UK visa routes most relevant to machine learning specialists, including eligibility criteria, application processes, and practical tips for a successful transition. Whether you’re an ML researcher, data scientist, AI engineer, or deep learning specialist, understanding the UK immigration framework is the first step to pursuing your career goals in Britain’s vibrant tech sector.

Leading UK Machine Learning Labs and Institutes: Pioneering the Future of AI

Over the past decade, machine learning (ML) has transformed from an academic field into a linchpin of commercial innovation. From personalised product recommendations to healthcare diagnostics, it fuels the algorithms behind every major breakthrough in the digital world. For data-driven enterprises and researchers, the United Kingdom offers a vibrant landscape of top-tier ML labs, academic institutes, and forward-looking industries. If you’re aiming to forge a career in this exciting domain—be it in cutting-edge research, industry applications, or policy-making—this comprehensive guide, written for MachineLearningJobs.co.uk, will walk you through the leading UK machine learning hubs. We’ll delve into the opportunities they present, the latest research challenges they tackle, and the career paths that await those ready to shape the future of AI.

Shadowing and Mentorship in Machine Learning: Gaining Experience Before Your First Full-Time Role

How to Find Mentors, Build Industry Connections, and Hone Your Technical & Soft Skills for a Thriving ML Career Machine learning (ML) is transforming industries at a rapid pace, fuelling breakthroughs in healthcare, finance, e-commerce, manufacturing, cybersecurity, and beyond. As the demand for ML expertise skyrockets, the competition for early-career opportunities has intensified. It’s not enough to complete an online course or a university degree; employers are looking for proven, hands-on experience. So, how do you stand out from the crowd? Two powerful strategies—shadowing and mentorship—can help you bridge the gap between academic theory and industry practice. By learning directly from experienced professionals, you gain practical insights and build the confidence needed to excel in real-world ML roles. In this in-depth guide, we’ll explore why mentorship is crucial, how to find the right mentors (both formally and informally), how to demonstrate your value as a mentee, and the best ways to shadow machine learning practitioners. By the end, you’ll be equipped with the knowledge and tactics to jump-start your career and secure your first full-time ML role.