Staff Robotics Engineer, AV Core

Posted 5 Days Ago
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London, Greater London, England, GBR
In-Office
Entry level
Artificial Intelligence • Transportation
The Role
Lead the technical strategy, design, and production integration of fault detection and fallback systems for autonomous vehicles. Develop robust robotics solutions, collaborate with machine learning and software teams, guide architecture decisions, and improve overall system safety and reliability. The role also involves mentoring, defining acceptance criteria, analyzing fleet data, and potentially building monitoring, debugging, and real-time systems for large-scale driverless vehicle operations.
Summary Generated by Built In
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!  

As a Staff Robotics Engineer in Wayve's AV Core organisation, you will lead the technical direction and delivery of fault detection and fallback systems for driverless operation. You will work alongside machine learning experts to build robust systems, and do some ML yourself. Physical AI is not just a learning problem; deployment in the real-world requires deep systems understanding of robotics.

The Core Model Safety team builds foundational capabilities for assisted and automated driving - collision avoidance, model understanding, and robustness under failure. You will work in a focused, high-impact senior team with strong ownership, access to large-scale training and fleet data, and close partners in research, simulation, evaluation, and applied engineering.

Key responsibilities

  • Set the technical strategy and roadmap for fault detection and fallback, from a robotics systems perspective, including its behavioral scope, operating envelope, system interfaces, and measurable acceptance criteria. 
  • Design and train fault detection mechanisms using the methods best supported by evidence to enable robust driverless operation. 
  • Collaborate across functions and expertise areas with machine learning, inference optimisation, software engineers, etc. 
  • Lead integration into the shared driving stack, align technical decisions across teams, and raise the bar through architecture reviews, mentoring, and clear communication of risks, trade-offs, and evidence. 
  • Use your judgement and expertise to improve the overall robustness of the robot system (beyond just fault detection and fallback). 

Essential 

  • Robotics: Proficiency in developing, implementing, and troubleshooting robotics solutions, backed by practical, real-world experience. 
  • A track record of staff-level technical leadership: setting direction for ambiguous programmes, aligning multiple teams, and carrying work from research through production deployment. 
  • Exceptional technical judgement and communication: able to make safety-relevant trade-offs explicit, define the evidence needed for decisions, and lead without relying on formal authority. 
  • Experience with Python and C++ for robotics. 

Desirable 

  • Operating robotics in the real world at scale: Proven experience in deploying and maintaining fleets of robots or vehicles under real-world conditions. 
  • Developing tooling to triage and debug robotic systems: Ability to create and refine data collection and analysis tools. 
  • Cloud infrastructure for monitoring: Experience setting up cloud-based monitoring solutions for large-scale fleets, including dashboards, logging, and real-time alerts. 
  • Knowledge of embedded / real-time systems: Familiarity with low-level hardware interactions and real-time constraints for safety-critical applications. 
  • Experience with machine learning and inference optimisation.

Wayve is committed to creating an inclusive interview experience. If you require any accommodations or adjustments to participate fully in our interview process, please let us know.

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.  

For more information visit Careers at Wayve. 

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

For US candidates only, please visit E-Verify Notice and Participation and Right to Work

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.



Skills Required

  • Practical experience developing, implementing, and troubleshooting robotics solutions
  • Staff-level technical leadership, including setting direction for ambiguous programs and aligning multiple teams
  • Experience carrying work from research through production deployment
  • Exceptional technical judgment and communication for safety-relevant trade-offs
  • Experience with Python and C++ for robotics
  • Experience deploying and maintaining fleets of robots or vehicles in real-world conditions
  • Ability to develop tooling for data collection, triage, and debugging robotic systems
  • Experience setting up cloud-based monitoring for large-scale fleets, including dashboards, logging, and real-time alerts
  • Familiarity with embedded or real-time systems and low-level hardware interactions
  • Experience with machine learning and inference optimization

Wayve Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Wayve and has not been reviewed or approved by Wayve.

  • Healthcare Strength Private healthcare and access to therapy via Spill are part of the standard package. This indicates robust health support within the core offering.
  • Leave & Time Off Breadth Paid vacation, public holidays, and additional leave programs are explicitly listed. This breadth of time away supports work–life balance expectations.
  • Equity Value & Accessibility Cash plus equity is standard in offers at this growth stage. This provides ownership alongside salary with perceived upside tied to company momentum.

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The Company
HQ: London
200 Employees
Year Founded: 2017

What We Do

We're Wayve, a leading developer of embodied intelligence for autonomous vehicles. We use AI to pioneer a next-generation approach to self-driving: AV2.0, which enables fleet operators to unlock the benefits of AV technology at scale. Founded in 2017, Wayve is made up of a diverse team of experts in machine learning and robotics. We were the first to deploy AVs on public roads with end-to-end deep learning. Today, our teams are based in London and California, and we're testing AVs in cities across the UK. Inspired by our vision for a smarter, safer, more sustainable world, we're looking for people who are passionate about building breakthrough solutions to some of the world’s most important challenges. If you're looking for an exciting opportunity with a dynamic team, get in touch!

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