Fleet Planning Engineer
Glydways
Who we are:
Glydways is reimagining what public transit can be. We believe that mobility is the gateway to opportunity—connecting people to housing, education, employment, commerce, and care. By making transportation more accessible, affordable, and sustainable, we empower communities to thrive and unlock economic and social prosperity.
Our mission is to revolutionize transit with a solution that delivers high capacity, exceptional user experiences, unmatched affordability, and minimal environmental impact.
The Glydways system is a groundbreaking network of carbon-neutral, interconnected transit pathways powered by standardized autonomous vehicles on dedicated roadways. Operating 24/7 with on-demand access, it offers personalized and efficient mobility—without the burden of heavy upfront infrastructure costs or ongoing taxpayer subsidies.
With Glydways, we’re building more than a transportation system; we’re creating a future where everyone, everywhere, has the freedom to move.
Meet the team:
You'll be joining a mission-driven autonomy engineering team focused on coordination, orchestration of resources, and task scheduling for autonomous vehicles. Our work spans from centralized fleet planning to onboard vehicle decision-making, blending algorithmic rigor with practical system implementation. We are passionate about building reliable, real-world autonomy solutions that can scale. The team values thoughtful design, clear documentation, and strong collaboration across disciplines including product, infrastructure, system engineering, and testing. We take pride in balancing deep technical expertise with a pragmatic approach to getting impactful solutions into production.
Required Skills:
- 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.
Roles and Responsibilities:
- 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.
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.