AI Engineer - Allocation and Packing Systems

Gallatin•El Segundo, CA

9d•$80,000 - $210,000

About The Position

Gallatin is rebuilding logistics infrastructure for the national security missions of the United States and allied partners. They build AI systems that determine how logistics decisions are made, operating at the layer where data becomes decisions and decisions make the advantage. This role focuses on developing and implementing AI systems for packing and allocation models for transport assets.

Requirements

Strong programming skills in Python or similar, with experience translating allocation logic into deterministic, testable production code.
Strong foundation in operations research, optimization, or applied algorithms for resource allocation and physical feasibility challenges.
Background in operations research, applied math, industrial engineering, or related fields.
Familiarity implementing allocation and assignment algorithms, including matching, prioritization, and constraint-based allocation under competing demands.
Experience modeling and solving packing problems, such as bin packing, knapsack, or multidimensional (2D/3D) packing problems.
Experience encoding capacity, compatibility, priority, and physical constraints in allocation and packing systems.
Familiarity with optimization techniques such as linear programming, mixed-integer programming, or heuristic and approximation methods for NP-hard problems.
Experience balancing solution quality, feasibility, and computational performance in large-scale or time-sensitive systems.
Experience with vehicle loading or palletization problems
Ability to reason about physical constraints and edge cases.
Comfort owning data pipelines and assumptions end-to-end.
Strong attention to correctness and failure modes.

Nice To Haves

Experience integrating packing with simulation systems.
Prior exposure to defense or government planning environments.
Experience with Machine Learning models, experimentation (e.g., A/B testing) and causal inference

Responsibilities

Build, maintain, and implement packing and allocation models for transport assets.
Encode constraints around volume, weight, compatibility, sequencing, and asset usage.
Weigh packing efficiency against runtime and real-world operational constraints.
Develop and refine heuristics or exact methods for solving packing and allocation problems.
Scale packing solutions across large fleets and dynamic inputs.
Evaluate tradeoffs between optimality, speed, and explainability.
Take ownership of the data inputs that feed allocation and packing - asset and supply attributes included.
Validate, normalize, and maintain packing-related datasets.
Manage edge cases and incomplete data directly.
Integrate packing outputs into resupply and routing workflows.
Collaborate with other teams to confirm physical executability of outputs.
Validate solutions through scenario testing and operational feedback.
Ensure AI-generated plans cannot bypass physical feasibility or constraint enforcement layers.