Description Beep is developing planning and orchestration platforms to facilitate the fleet-scale management of multi-passenger autonomous vehicles, with a focus on integration with existing public transit operations. The R&D Intern will aid the R&D team with their expertise in fleet management for public transit, responsible for algorithm development for demand forecasting, path and fleet planning, vehicle assignment, dispatch, routing, rebalancing, and block scheduling. They will work to design and implement services to enable optimization of autonomous fleets within Beep’s autonomous software platform. This is a part-time internship position located in Atlanta, GA. Responsibilities: Develop transit optimization algorithms for Beep’s autonomous services platform Serve as a subject matter expert for approaches to public transit operations and optimization Aid Beep’s R&D team with the design and implementation of optimization and ML services for Beep’s autonomous service platform Contribute to the development of research publications, white papers, and intellectual property filings Requirements Exposure to public transit operations, associated data sets, models, and data exchange protocols Experience developing forecasting and clustering algorithms Experience developing simulation and algorithm validation frameworks Experience developing algorithms for vehicle or fleet planning Familiarity working in an Agile development environment Fluency in at least one scripting or analytical language High attention to detail and accuracy, especially in verbal and written communication Self-starter, excellent problem solver, flexible, resourceful, process driven, and have a high degree of integrity and ethics Comfort dealing with ambiguity and the ability to work independently Interest in emerging technology and mobility solutions Education and Experience: Bachelor of Science degree in a STEM field Current PhD student in Engineering, Mathematics, or Computer Science OR a Master's degree in Engineering, Mathematics, or Computer Science Well qualified candidates will have expertise in Operations Research Work or project experience related to mobility or public transit Experience with large-scale data analysis and simulation Experience developing POC software implementations Experience working in an Agile development environment Prior publications in the field; please provide references with CV or resume Physical Requirements: Prolonged periods of sitting, predominately in an office environment