Staff Embedded Software Engineer, Automotive Platforms

Wayve; Greater London; Hybrid; GBP 110,000 - 170,000; Full time

Benefits offered by this job

Equity (meaningful)

Relocation support & visa sponsorship

Hybrid working

Learning & development budget

Health insurance

Retirement/pension

Job summary

Wayve is seeking a Staff Software Engineer to lead significant embedded software work connecting our AI Driver to vehicle platforms. You will shape software architecture, drive design decisions and ensure reliable integration across hardware and software layers.

The role requires strong C++ skills, experience with embedded systems, Linux/QNX environments, and collaboration across autonomy, hardware and product teams to deliver robust capabilities for real vehicles.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical, Automotive Engineering or related field, or equivalent practical experience.
• Strong software engineering experience in modern C++, delivering production-quality software.
• Experience developing embedded or systems software on Nvidia and Qualcomm platforms with Linux/QNX.
• Experience with Linux-based platforms and system architecture design.

Responsibilities

• Design, build and maintain embedded software integrating Wayve’s AI Driver with vehicle platforms and onboard systems.
• Develop interfaces between AI capabilities, vehicle software and platform components.
• Collaborate across autonomy, hardware, vehicle programmes and product to clarify requirements and resolve integration issues.

Skills

C++ expertise

Embedded software

Linux systems

System architecture

Debug & testing

Cross-team collaboration

NVIDIA/Qualcomm platforms

Education

BSc/MSc in CS/EE/Automotive

Tools

Linux

QNX

Embedded toolchains

Job description

Wayve is seeking a Staff Software Engineer to lead significant embedded software work connecting our AI Driver to vehicle platforms. You will shape software architecture, drive design decisions and ensure reliable integration across hardware and software layers.

The role requires strong C++ skills, experience with embedded systems, Linux/QNX environments, and collaboration across autonomy, hardware and product teams to deliver robust capabilities for real vehicles.