Staff Robotics Engineer, AV Core

Wayve
London, United Kingdom
On-site

Who this role is best for

Geared toward technical leaders comfortable with fault detection and fallback systems, working in a collaborative, hybrid environment in London.

Best fit for

  • Candidates with staff-level technical leadership experience in robotics and AI deployment
    β€” β€œA track record of staff-level technical leadership: setting direction for ambiguous programmes”
  • Individuals with hands-on experience deploying and maintaining fleets of robots or vehicles
    β€” β€œExperience deploying and maintaining fleets of robots or vehicles at scale under real-world conditions”
  • Candidates with strong technical judgment and ability to communicate safety trade-offs
    β€” β€œStrong technical judgement and communication, able to make safety-relevant trade-offs explicit”

Things to consider

  • Requires working in both Python and C++ for robotics development
    β€” β€œComfortable working in Python and C++ for robotics”
  • Candidates should be prepared for integration work across multiple engineering disciplines
    β€” β€œCollaborate across functions and expertise areas, including machine learning, inference optimisation, and software engineering”

How to stand out

  • Highlight experience in setting technical strategies for fault detection and fallback systems
    β€” β€œSet the technical strategy and roadmap for fault detection and fallback”
  • Emphasize cross-functional collaboration and leadership in architecture reviews
    β€” β€œLead integration into the shared driving stack, align technical decisions across teams”
  • Showcase ability to improve system robustness beyond fault detection
    β€” β€œUse your judgement and expertise to improve the overall robustness of the robot system”
Pace Β· SteadyCollaboration Β· HighAutonomy Β· MediumDecision Impact Β· Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • reliable fault detection systems
  • improved vehicle safety
Typical background
robotics engineerautonomous vehicle developer

Skills & requirements

Required

RoboticsAutonomous DrivingFault DetectionModel UnderstandingSystem IntegrationPythonC++Fleet Management

Preferred

Embedded SystemsMachine LearningInference OptimizationCloud-based MonitoringTooling Development

Stack & domain

Robotics SolutionsTechnical LeadershipPython And C++ For RoboticsDeploying And Maintaining Fleets Of Robots Or VehiclesTooling For Triaging And Debugging Robotic SystemsEmbedded Or Real-time SystemsMachine Learning And Inference OptimisationCommunicationProblem-solvingTeamworkAutonomous VehiclesAIRobotics

About the role

Original posting from Wayve via Ashby

Before the detail, here's the challenge you'd help us solve.

We build the embodied intelligence that moves real vehicles safely, and the ecosystem a billion machines will run on in the future. Very few people in AI can say this. Every role here, whatever the team, plugs into that.

Here’s what this particular role covers.

πŸ› οΈ About our Core Model Safety Team

The Core Model Safety team builds foundational capabilities for assisted and automated driving, including collision avoidance, model understanding, and robustness under failure. It's a small, high-impact team with strong ownership, access to large-scale training and fleet data, and close partners across research, simulation, evaluation, and applied engineering. The work here is central to making driverless autonomy possible: detecting and preventing collisions, developing emergency-driving behaviours from limited data, and making sure the vehicle responds safely when something goes wrong.

🧠 Your day-to-day

  • Set the technical strategy and roadmap for fault detection and fallback, including its behavioural 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, including machine learning, inference optimisation, and software engineering
  • 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

🧩 What you'll be working on:

  • Fault detection and fallback systems that let the vehicle respond safely when something goes wrong, from strategy through to deployment on the car
  • Collision avoidance, model understanding, and robustness under failure: the foundational capabilities this team owns for assisted and automated driving
  • Fault detection methods chosen on the strength of evidence, built to hold up under real driverless operation
  • Integration into the shared driving stack, working closely with machine learning, inference optimisation, and software engineering partners
  • Large-scale training and fleet data, with close partners in research, simulation, evaluation, and applied engineering

πŸ‘€ You should apply if:

  • Proficient 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
  • Strong technical judgement and communication, able to make safety-relevant trade-offs explicit and lead without relying on formal authority
  • Comfortable working in Python and C++ for robotics
  • Experience deploying and maintaining fleets of robots or vehicles at scale under real-world conditions
  • Bonus if you've built tooling to triage and debug robotic systems, or set up cloud-based monitoring for large-scale fleets
  • Familiarity with embedded or real-time systems, or hands-on machine learning and inference optimisation experience, is a plus

🌱 Not ticking every box? That's totally okay! If you're passionate about autonomy and keen to learn, we encourage you to apply even if you don't meet every requirement.

More about Wayve:

πŸš— Wayve is building the leading AI platform for autonomous driving. We are pioneering an end to end AI approach that enables vehicles to learn directly from real world experience, developing the ability to adapt, generalise and improve at scale. Instead of relying on hand coded rules or pre mapped environments, our AI Driver learns to drive by understanding the world around it. The result is technology that navigates complex urban environments with intelligence, precision and natural flow, unlocking meaningful advances in both safety and efficiency. We believe autonomy represents a once in a generation transformation in how people and goods move, comparable to the shift from horses to cars, and from human driven vehicles to intelligent machines.

Our ambition is to make autonomy universal. Wayve's mapless and hardware agnostic AI platform integrates with global OEM partners, enabling continuous software evolution and unlocking advanced levels of automation from L2 plus through to L4 as our core AI model scales. In a race increasingly defined by intelligence and real world learning, Wayve is taking a distinct approach, building a generalisable driving intelligence that can power any vehicle, anywhere. By combining embodied AI with scalable deployment, we are creating technology that can be shaped to each OEM brand and driver experience, accelerating the transition to a safer, more intelligent future of mobility.

How we work πŸ’» β€” Locations & Flexible Working:

Our main hubs are in London, Sunnyvale, Yokohama, Herzliya, Vancouver and Leonberg. We operate a hybrid working model that combines in-person collaboration in our dedicated office spaces with focused time working remotely. This gives our teams the connection and energy of working together, alongside the flexibility to do their best work in a way that fits their lives.

πŸ“‹ The Interview Process:

Our process is clear and respectful of your time:

  • Initial call / recruiter screen (30 mins)
  • Hiring manager interview (30 mins)
  • Deep-dive technical interviews ( Tech Leadership, Domain, Programming; 3 hours)
  • Final interview: mission & values alignment (1 hour)

We'll always explain the format and work around your availability.

What's in it for you (Location dependent):

πŸ’° Salaries benchmarked against the market annually

πŸ“ˆ Meaningful equity, sharing in the ownership and long term success of Wayve

✈️ Relocation support and visa sponsorship where applicable

βœ… Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs

πŸ“š Learning and development budgets with support for training, conferences and growth

🩺 Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partner discounts and more

A quick, honest note before you apply.

Wayve is not a mature, fully-structured place with the playbook already written. Much of how we work is still being written, and if you join, you’ll help write it. That suits people who want real ownership more than people who need a settled structure from day one.

If that sounds like the kind of problem you want to spend your time on, we’d really like to hear from you.

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. https://wayve.ai/careers/ To learn more about what drives us, visit Values at Wayve https://wayve.ai/careers/

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.

Source: Wayve careers (Ashby)

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