The role involves partnering with engineering teams to design, test, and deploy machine learning and generative AI models to improve issue detection and quality assurance. The individual will leverage AI-powered insights to identify on-road trends and risk scenarios while defining policies and standard operating procedures for international markets. A key responsibility includes serving as a bridge between AI development and operational execution to ensure seamless integration of new tools. The position requires designing robust quality control processes for both human and AI-generated outputs. Additionally, the role provides technical leadership to stakeholders and drives user testing for new tooling features.

Candidates must possess a BS/BA degree or at least eight years of relevant work experience in autonomous vehicle software quality operations. A strong understanding of driving rules and regulations in London is required, alongside competency in the machine learning development lifecycle. Applicants need experience with ML testing, validation, and performance evaluation using statistical metrics. The role demands the ability to work in a fast-paced environment and excellent communication skills for cross-functional collaboration.