Autonomous Driving Forensics Engineer β€” Data-Driven Debugging

Autonomous Driving Forensics Engineer β€” Data-Driven Debugging

Full-Time 51102 - 62458 Β£ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Investigate and debug issues in autonomous driving technology to enhance performance.
  • Company: Wayve, a leader in autonomous driving innovation.
  • Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Collaborative environment with cross-functional teamwork and exciting challenges.
  • Why this job: Join a dynamic team and make a real impact on the future of transport.
  • Qualifications: Experience in debugging and a passion for autonomous systems.

The predicted salary is between 51102 - 62458 Β£ per year.

Wayve is seeking an Autonomous Driving Forensics Engineer to join the Detectives team within the Model Integration and Release group.

You will investigate issues across the full AV stack, identify root causes, test solutions, and provide actionable insights to improve performance.

The role sits at the heart of performance improvement, requiring cross-functional engagement with hardware, software, model development, operations and safety teams.

Hybrid work from our London office is offered.

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Autonomous Driving Forensics Engineer β€” Data-Driven Debugging employer: AI Startups UK

Lovable is an exceptional employer for data scientists, particularly in our dynamic London growth team. With a culture of extreme ownership and low-ego collaboration, we empower our employees to drive impactful growth metrics while working alongside talented engineers. Our commitment to innovation and rapid experimentation offers unparalleled opportunities for professional development, making Lovable a truly rewarding place to build your career.

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Contact Details:

AI Startups UK Recruitment Team

We think you need these skills to ace Autonomous Driving Forensics Engineer β€” Data-Driven Debugging

SQL
Problem-Solving Skills
Communication Skills
Python
Automation
Attention to Detail
Data Engineering