The role involves partnering with engineering teams to design, test, and deploy machine learning and generative AI models to improve issue discovery and quality assurance. The individual will leverage AI-powered insights to identify on-road risk scenarios and emerging trends. Responsibilities include defining and documenting policies and standard operating procedures that integrate AI tools into daily workflows. The position requires designing quality control processes for both human and AI-generated outputs. Additionally, the role acts as a subject matter expert to ensure the adoption of AI advancements within quality operations. The individual will provide technical leadership by identifying tool issues and driving user testing for new features.

The role requires a BS/BA degree and four years of relevant work experience in autonomous vehicle software quality operations. Candidates must demonstrate competency in the machine learning development life cycle, including data preparation, training, validation, and monitoring. Proficiency in ML testing, bias detection, and performance evaluation using statistical metrics is necessary. Additionally, the position requires basic SQL and PLX coding skills, along with an understanding of driving rules and regulations.