Engineering Manager - Autonomous Driving Forensics - Remote

Overview

As the Engineering Manager - Autonomous Driving Forensics Engineer, you will lead a cross-functional team focused on identifying and resolving systemic issues in autonomous vehicle (AV) performance. Leveraging your expertise in robotics and AI, you will provide actionable insights that drive improvements in our end-to-end AV stack, empowering development teams to deliver world-class performance.

In Short

• Lead cross-functional teams to identify, analyse, and resolve complex performance issues in AV systems.
• Apply your robotics and AI expertise to investigate systemic issues across the AV stack.
• Design and oversee experiments to test hypotheses and improve system performance.
• Leverage video, simulation, and telemetry data to identify trends and root causes.
• Communicate findings and strategies to technical and non-technical stakeholders.
• Drive statistical rigour and best practices in performance analysis and experimentation.
• Collaborate with developers to implement solutions and track performance improvements.

Requirements

• 5+ years of experience working with complex robotics or AI systems, including leadership roles.
• Proven ability to design experiments for real-world robotic systems and analyse their results.
• Exceptional problem-solving and critical thinking skills to address complex technical challenges.
• Strong communication skills for engaging with both technical and non-technical audiences.
• Experience with statistical scripting and data analysis tools (e.g., Python with pandas, sklearn, scipy).
• Proficiency in remote Linux environments and hands-on debugging.
• Demonstrated ability to influence organisational direction through actionable insights.

Benefits

• Hybrid working policy combining office and remote work.
• Core working hours for flexible scheduling.
• Inclusive work environment valuing diversity and unique perspectives.
• Opportunity to work on cutting-edge AI technology.
• Impactful role in the development of autonomous driving systems.