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Salary
$150k – $271k per year (Estimated)
Location
Remote/Hybrid (London, United Kingdom)
Seniority
Senior · 5+ years exp
Overview
Company
Impact
Profile match
Wayve is a British autonomous driving technology company that develops end-to-end "Embodied AI" foundation models for self-driving vehicles and advanced driver assistance systems (ADAS). Founded in 2017 by University of Cambridge researchers, Wayve pioneered what it calls the "AV2.0" approach to autonomous vehicles. Unlike traditional self-driving stacks that rely on rigid hand-coded rules, high-definition (HD) 3D maps, and specialized sensors, Wayve uses a unified deep learning model.

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!

The role

As a software engineer for Wayve’s Simulation Technology team, you will be an expert software engineer who evolves a core component of Wayve’s simulation platform, which is used to develop and evaluate Wayve’s driving intelligence.

Wayve’s approach to autonomous driving presents unique challenges for simulation. Our end to end driving stack requires a simulator that is both highly realistic and highly descriptive. Our approach to simulation brings together a combination of classical simulation techniques with cutting edge developments in machine learning to represent the real world in high fidelity at scale.

You will be responsible for shaping and implementing the technical roadmap in one of three key areas: robot emulator fidelity, visual fidelity, or efficient scaling. You will be working closely with our robotics, research, platform and data teams, as well as the rest of the Simulation Technology team to ensure that our simulation platform meets the needs of our end-users by providing accurate, scalable, and high-signal simulations.

Challenges you will own

  • Own key performance indicators (KPIs) for simulator cost, SLOs, throughput, latency, etc.
  • Work cross-company on aligning technical dependencies for simulator implementation
  • Lead technical discussions and guide technical direction
  • Effectively integrate the components of the simulated robot into the simulation platform
  • Effectively integrate machine-learned graphics subsystems into the simulation platform
  • Implement production quality software in Python

About you

Essential

  • Experience with workflow orchestration systems (e.g. Airflow, Dagster, Flyte, etc.) and/or developing data intensive applications
  • Excellent development skills in Python
  • Deep knowledge of Kubernetes at the user level
  • Good sense of systems and data oriented software engineering design - what makes code reusable and extensible
  • Understanding of common software performance issues and design tradeoffs
  • 5+ years of industry experience designing and programming software
  • Excellent communication and people engagement skills

Desirable

  • Experience in the field of autonomous vehicles or robotics
  • Proficiency with other programming languages like go or C++
  • Experience scaling simulations or data intensive workloads
  • Experience with design, implementation, and optimization of large-scale machine learning inference systems running in cloud GPU environments
  • Experience operating and scaling modern machine learned graphics techniques (NeRF, Gaussian Splatting, or GenAI)

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. We operate core working hours so you can determine the schedule that works best for you and your team.

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.

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