The role involves leading the development of machine learning models to automate high-volume workflows and enhance human-led triaging. The position focuses on designing and building generative AI solutions for behavior analysis and anomaly detection in autonomous vehicles. Responsibilities include developing reinforcement learning systems based on human preferences and enhancing user feedback analysis through various classification and summarization techniques. The role also entails overseeing the production and optimization of machine learning models to assess a large fleet of vehicles. Furthermore, the individual will drive technical direction and collaborate with cross-functional teams to align technical agendas with business objectives.

Candidates must possess a B.S. in Computer Science, Robotics, Machine Learning, or a related field, or have equivalent practical experience. A minimum of 7 years of hands-on experience in machine learning projects is required, along with strong coding proficiency in C++ or Python. Expertise in deep learning models, ML deployment at scale, and specific frameworks like TensorFlow or PyTorch is necessary. An M.S. or Ph.D. in a quantitative field and 10+ years of experience are preferred.