The role involves designing, implementing, and evaluating algorithms and models to enhance pick-up and drop-off point selection and routing quality. The individual will develop and improve simulation and evaluation infrastructure to measure the impact of changes and accelerate development cycles. Responsibilities include analyzing large datasets from the vehicle fleet to identify opportunities and guide product direction. The position requires collaboration with various internal teams to ensure a cohesive user experience. The individual will contribute to the full software development lifecycle, encompassing ideation, design, implementation, testing, deployment, and monitoring.

Candidates must possess a Bachelor's degree in Computer Science or a related field, or equivalent practical experience. The role requires at least seven years of software engineering experience, specifically in designing and building production-grade systems. Applicants must have a minimum of three years of experience in developing and deploying machine learning models in real-world applications. Proficiency in C++ and the ability to work with large datasets using tools like SQL or Plx are mandatory. A Master's or PhD in a relevant field is preferred.