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Gallatin is rebuilding logistics infrastructure for U.S. national security missions. The company builds AI systems that determine how logistics decisions are made at scale, operating at the layer where data becomes decisions.
In this role, you will own the design and implementation of routing and network optimization systems that determine how supplies, vehicles, and materiel move across Gallatin's global distribution networks. You will build systems that handle time-phased, capacity-constrained, and risk-aware routing at scale, turning AI-driven intent and operational demand into optimal, executable routes across thousands of assets and nodes.
Key responsibilities include:
- Design and implement routing models across transportation, warehousing, and resupply networks, encoding constraints related to distance, time, availability, readiness, risk, asset capacity, and lane capacity.
- Support multi-hop, event-aware, and time-phased routing across dynamic networks.
- Implement and tune routing solvers using exact, heuristic, and hybrid algorithms, scaling to large graphs, real-time updates, and uncertain inputs.
- Evaluate tradeoffs between solution quality, runtime, and operational robustness.
- Own routing datasets including nodes, edges, costs, capacities, and constraints; validate and maintain network representations used by all routing and planning systems.
- Handle data gaps, uncertainty, and changing network conditions without breaking execution.
- Integrate routing systems into batch and real-time planning pipelines.
- Partner with feasibility, simulation, and execution teams to validate route executability.
- Support scenario testing, what-if analysis, and iterative optimization based on real operational feedback.
You will work closely with feasibility, packing, optimization, and AI-agent teams to ensure routing decisions are correct, scalable, and resilient under real-world operational volatility.
REQUIREMENTS:
- Strong programming skills in Python or similar, with experience translating mathematical models into production-grade systems.
- Experience integrating routing or optimization algorithms into live planning pipelines with monitoring, validation, and performance tuning.
- Degree or equivalent experience in Operations Research, Applied Math, Industrial Engineering, Computer Science, or related field.
- Strong foundation in graph theory, network optimization, shortest-path algorithms (Dijkstra, A*, Bellman-Ford), and network flow models (max flow, min cut, min-cost flow).
- Experience with vehicle routing problems (VRP), capacitated routing, or routing with time windows.
- Experience with large-scale graphs, time-expanded networks, or multi-commodity flow models.
- Hands-on experience with modeling languages and solvers such as Pyomo, GAMS, AMPL, CPLEX, or Gurobi.
- Ability to reason about scale, uncertainty, and time-dependent systems.
- Strong focus on performance, correctness, and reliability in high-stakes environments.
- Comfort owning routing logic and data end-to-end.
BONUS:
- Experience with vehicle routing or transportation systems.
- Experience working alongside simulation or digital-twin teams.
- Exposure to defense, government, or mission-critical logistics.
- Experience with ML models, experimentation (A/B testing), or causal inference.
- Experience with data operationalization and production analytics.
Note: This position may require the ability to obtain and maintain a U.S. government security clearance and work in classified environments. U.S. citizenship is a requirement for all positions at Gallatin.
