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Gallatin AI, Inc. · 12 hours ago

AI Engineer-Allocation and Packing Systems

El Segundo, CA

Full-time

Onsite

Mid Level

Gallatin AI, Inc. is seeking an AI Engineer to own allocation and packing models for their resupply systems. This role involves building decision systems that translate AI reasoning into executable logistics plans, focusing on the physical assignment of supplies within real-world constraints.

LogisticsMilitaryNational SecurityPredictive AnalyticsSoftwareSupply Chain Management

Responsibilities

Design and implement packing and allocation models for transport assets

Encode constraints related to volume, weight, compatibility, sequencing, and asset usage

Balance packing efficiency with runtime and operational realism

Implement and tune heuristics or exact approaches for packing and allocation problems

Scale packing solutions across large fleets and dynamic inputs

Evaluate tradeoffs between optimality, speed, and explainability

Own data inputs required for allocation and packing, including asset and supply properties

Validate, normalize, and maintain packing-related datasets

Manage edge cases and incomplete data directly

Integrate packing outputs into resupply and routing workflows

Partner with teams to validate physical executability

Validate solutions through scenario testing and operational feedback

Ensure AI-generated plans cannot bypass physical feasibility or constraint enforcement layers

Qualification

PythonOperations researchOptimization techniquesAllocation algorithmsPacking problemsData managementSystems thinkingMachine LearningAttention to detail

Required

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 problems

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