Fleet Planning Engineer

Job not on LinkedIn

November 13

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Logo of Glydways

Glydways

Transport • Artificial Intelligence • B2C

Glydways is a company focused on transforming public transit through innovative and efficient mobility solutions. Their unique approach includes a seamless self-driving fleet operating on dedicated guideways, allowing for direct and congestion-free rides. Glydways aims to make transit accessible and financially sustainable, promoting the idea that access to mobility is essential for opportunity and community engagement.

51 - 200 employees

Founded 2016

🚗 Transport

🤖 Artificial Intelligence

👥 B2C

📋 Description

• 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. • Implement feedback-based strategies to maintain stable fleet utilization. • Build mathematical and simulation models representing vehicle movement, demand patterns, and station queues. Derive and maintain performance metrics (e.g., wait time, idle miles, fairness, stability). • Analyze fleet utilization, imbalance, and throughput to identify bottlenecks or inefficiencies. • Conduct what-if studies using simulated origin/destination demand matrices, travel times, and network layouts to stress-test load-balancing strategies.

🎯 Requirements

• 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). • Ability to design or interpret simulation experiments to evaluate routing or balancing strategies. • Comfortable deriving or reasoning with continuous relaxations of discrete problems. • Experience with stochastic or probabilistic modeling (Poisson processes, demand forecasting). • Knowledge of graph algorithms (shortest path, matching, network flow). • Strong programming proficiency in Python or C++, including writing efficient, numerically stable algorithms. Experience with modern build/test tooling (e.g., Bazel). • Systems reliability and operations mindset: observability, debugging at scale, graceful degradation, and deployment patterns.

🏖️ Benefits

• Glydways provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

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