Full-Time

Tech lead – Automotive Onboard Software

Confirmed live in the last 24 hours

Wayve

Wayve

201-500 employees

Develops autonomous vehicle technology using AI

Automotive & Transportation
AI & Machine Learning

Senior, Expert

London, UK

Hybrid working policy requires time in the London office.

Category
Embedded Engineering
Software Engineering
Required Skills
Rust
AUTOSAR
C/C++
Linux/Unix
Requirements
  • Extensive experience in developing and deploying safety-critical automotive embedded software in C++ for automotive products, with a proven track record of leading large technical programs and teams
  • Deep understanding and experience with ASPICE-compliant Software Development Life Cycle (SDLC) processes
  • Expertise in creating embedded software using the AUTOSAR architecture
  • Strong leadership qualities, capable of leading cross-functional teams and projects. Excellent ability to collaborate across divisions and effectively engage stakeholders
  • Effective communication skills, capable of conveying complex technical and business concepts to a broad audience
  • Bachelor’s degree in Computer Science, Electrical Engineering, or a related field, or equivalent professional experience
  • Expertise and proficiency in using both C++ and Rust for embedded software development
  • A Master’s degree or greater in Computer Science, Electrical Engineering, or a related field
  • Strong background in developing software for a variety of automotive embedded systems and operating systems, notably Linux and QNX
  • Experience with L2-L3 autonomous driving applications and integrating ML-based AD solutions into automotive systems
  • Familiarity with ISO 26262 functional safety standards
Responsibilities
  • Independently lead extensive areas of embedded software development and critical automotive programs. Ensure timely delivery by effectively managing requirements, technical risks, development strategies, milestones, and dependencies, with a strong focus on safety and compliance
  • Design and develop software architecture to integrate our machine learning-based autonomous driving solution into an automotive L2-L3 system application. Ensure seamless integration with OEM software environments to enable full sensor integration and data capture at the scale and quality necessary for a fully autonomous vehicle
  • Work closely with cross-functional teams comprising machine learning engineers, software developers, system engineers, and product managers to define and refine the software architecture
  • Collaborate with safety and functional safety teams to ensure the software architecture aligns with ISO 26262 functional safety standards and other relevant regulations. Support the team in implementing ASPICE compliant processes
  • Maintain a robust, compliant, and scalable code base for embedded systems, fostering rapid development and future scalability
  • Deliver and maintain real-time Linux-based and QNX-based applications for a fleet of embedded devices on automobiles, including data collection, storage, and machine learning inference on the edge
  • Develop and implement fault-tolerant software solutions with comprehensive system diagnostics to quickly identify and resolve issues in deployed automotive systems
  • Provide mentorship to engineers, guiding them in their professional growth. Actively lead forums such as design reviews and architecture planning to promote a culture of engineering excellence and compliance

Wayve.ai develops self-driving technology known as AV2.0, which focuses on creating smarter and safer autonomous vehicles. Their technology uses embodied AI software that allows vehicles to learn from their experiences and adapt to different environments without needing detailed programming. This method is different from traditional self-driving technologies that often rely on expensive hardware and pre-mapped data. Instead, Wayve.ai employs end-to-end deep learning, making their solution more cost-effective for automakers. The company targets automakers and fleet operators, offering them adaptable and affordable solutions for driving automation. Wayve.ai aims to enhance mobility by partnering with companies like Ocado Group and Asda to test their technology in real-world delivery scenarios.

Company Stage

Series C

Total Funding

$1.3B

Headquarters

London, United Kingdom

Founded

2017

Growth & Insights
Headcount

6 month growth

38%

1 year growth

59%

2 year growth

115%
Simplify Jobs

Simplify's Take

What believers are saying

  • Wayve.ai's recent $1.05 billion funding round underscores strong investor confidence and provides substantial capital for further innovation and expansion.
  • The launch of PRISM-1, a 4D reconstruction model, enhances the testing and training of their autonomous driving technology, potentially accelerating development timelines.
  • Partnerships with major retailers and fleet operators offer significant opportunities for real-world testing and rapid deployment of their technology.

What critics are saying

  • The autonomous vehicle sector is highly competitive, with major players like Tesla and Nvidia investing heavily in similar technologies, which could impact Wayve.ai's market share.
  • The reliance on end-to-end deep learning and embodied AI, while innovative, may face challenges in regulatory approval and public acceptance.

What makes Wayve unique

  • Wayve.ai's use of embodied AI software allows vehicles to learn and adapt from experience, eliminating the need for costly HD maps and human-engineered systems, unlike traditional autonomous vehicle technologies.
  • Their end-to-end deep learning approach reduces the reliance on expensive robotic stacks, making their solution more cost-effective for automakers.
  • Wayve.ai's partnerships with leading UK retailers like Ocado Group and Asda for trialing their technology in delivery fleets demonstrate their practical, real-world application and scalability.

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