Glydways · 8 hours ago
Software Engineering Intern (Dispatch – Fleet Optimization)
United States
Internship
Remote
InternGlydways is reimagining public transit to enhance mobility and connect communities. The Software Engineering Intern will collaborate with the Dispatch team to prototype fleet optimization algorithms and contribute to system performance through simulation experiments and code development.
Clean EnergyElectric VehicleManufacturingTransportation
Responsibilities
Prototype and evaluate fleet optimization algorithms for problems like vehicle rebalancing, charging strategies, and maintenance/cleaning scheduling (e.g., using mixed-integer optimization, dynamic programming, or heuristic/metaheuristic methods)
Explore reinforcement learning–based approaches for selected dispatch decisions (e.g., when to send vehicles to charge, how to route vehicles through busy junctions), including state representation, reward design, and basic policy evaluation in simulation
Design and run simulation experiments to compare algorithm variants (optimization- or RL-based) using metrics such as wait time distributions, fleet utilization, energy usage, and robustness under disruptions
Contribute production-quality code to the Dispatch codebase in C++ and/or Python, including unit tests, integration tests, and clear documentation
Collaborate with teammates to translate high-level operational or commercial questions (e.g., “How many vehicles do we need for this project?” or “What if charging is slower?”) into well-posed optimization or simulation studies
Work with other autonomy and platform teams to understand constraints coming from motion limits, energy usage, and infrastructure design, and incorporate them into your models and algorithms
Participate in code reviews and design discussions, giving and receiving feedback to improve both code quality and overall system design
Qualification
Required
Academic background in computer science, operations research, robotics, electrical engineering, applied mathematics, or a related field
Current undergraduate (rising senior) or graduate student status (MS or PhD) with relevant coursework or research in optimization and/or reinforcement learning
Solid programming skills in at least one of: C++ (preferred for production code), and/or Python (preferred for prototyping, data analysis, and RL/optimization experiments)
Coursework or experience in optimization, such as: Linear / integer / mixed-integer programming, Dynamic programming, approximate dynamic programming, or stochastic optimization, Heuristics or metaheuristics (e.g., simulated annealing, genetic algorithms, search-based methods)
Coursework or experience in reinforcement learning, such as: Markov decision processes, value-based and/or policy-based methods, Function approximation (e.g., neural networks) and experience with a framework like PyTorch or TensorFlow is a plus, Experience training and evaluating RL policies in simulated environments is a plus
Strong grasp of algorithms, data structures, and complexity, and comfort reasoning about performance trade-offs in large-scale systems
Familiarity with probability, statistics, and simulation, including designing experiments and interpreting results
Software engineering fundamentals: Comfort working in a Linux environment, Experience with version control (git) and collaborative development workflows, Writing clear, maintainable, and tested code
Ability to communicate technical ideas clearly, both in writing and in discussions, and to collaborate effectively with teammates from different disciplines
Company
Glydways
Glydways designs and implements personal rapid transit systems using self-driving vehicles.
Founded in 2016
51-200 employees
H1B Sponsorship
Glydways has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (10)
2024 (5)
2023 (2)
Funding
Current Stage
Growth StageTotal Funding
$212.54M2025-09-29Series Unknown· $101.31M
2024-05-14Series B· $20M
2023-10-05Series B· $56M
Leadership Team
Gokul Hemmady
CEO
Chris Riley
Chief Commercial Officer
Recent News
2025-11-14
2025-11-01
Company data provided by crunchbase