Staff Robotics Engineer, AV Core

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 an

• 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).

• 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.