The role involves leading the development of deep learning and machine learning models to automate high-volume workflows and enhance human-led triaging. The individual will design systems for data collection and evaluation based on reinforcement learning from human preferences. Responsibilities include enhancing user feedback analysis through tools for sentiment assessment, comment summarization, and root cause analysis. The position requires overseeing the production and optimization of models to assess the performance of a large vehicle fleet. Furthermore, the role involves driving technical direction and collaborating 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 similar technical field, or equivalent practical experience. The role requires at least five years of hands-on experience in machine learning projects and strong coding proficiency in C++ or Python. Applicants must demonstrate experience in foundational models, VLM, or deep learning, along with expertise in ML frameworks and deployment at scale. An M.S. or Ph.D. in a quantitative field with a specialization in machine learning is preferred.