Fleet Planning Engineer

• Design and implement algorithms that dynamically allocate vehicles to meet time-varying passenger demand.
• Formulate and solve optimization problems (e.g., MILP, QP, network flow) for vehicle routing, rebalancing, and resource allocation.
• Develop heuristics or approximations for real-time decision-making when full optimization isn’t tractable.
• Build mathematical and simulation models representing vehicle movement, demand patterns, and station queues.

This role creates positive change by developing autonomous vehicle systems that make transportation more accessible, affordable, and sustainable, empowering communities to thrive and unlocking economic and social prosperity through carbon-neutral transit solutions.

• Strong grounding in linear, integer, and quadratic programming (e.g., MILP, QP, LP solvers like Gurobi, OSQP, or CPLEX).
• Familiarity with Model Predictive Control (MPC) and dynamic resource allocation methods.
• Understanding of queueing systems and flow equilibrium models (for balancing supply vs demand).
• Strong programming proficiency in Python or C++, including writing efficient, numerically stable algorithms.

No specific benefits, compensation, or salary information mentioned in the job description.

Glydways is reimagining public transit with a mission to revolutionize transportation through a carbon-neutral, interconnected transit system using standardized autonomous vehicles on dedicated roadways, aiming to create a future where everyone has the freedom to move.