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 identify emerging on-road trends and risk scenarios by leveraging AI-powered insights and traditional triage signals. Responsibilities include defining and documenting standard operating procedures that integrate AI tools into vendor workflows. The position requires designing quality control processes for both human and AI-generated outputs while performing meta-quality checks. Additionally, the role serves as a subject matter expert to ensure the seamless adoption of AI advancements across operational teams. The individual will provide technical leadership by identifying tool issues and driving user testing for new features.

Candidates must possess a BS/BA degree or four years of relevant work experience in autonomous vehicle software quality operations. Required qualifications include competency in the machine learning development lifecycle and experience with ML testing, validation, and performance evaluation. Applicants must demonstrate the ability to learn proprietary tools and possess a strong understanding of driving regulations. The role requires the flexibility to work weekends and holidays as needed.