AI Engineer - Allocation and Packing Systems

The role

The AI Engineer will build, maintain, and implement packing and allocation models for transport assets. They will develop algorithms, manage data inputs, and integrate outputs into resupply and routing workflows.

What you will do

• Build, maintain, and implement packing and allocation models for transport assets.
• Encode constraints around volume, weight, compatibility, sequencing, and asset usage.
• Develop and refine heuristics or exact methods for solving packing and allocation problems.
• Scale packing solutions across large fleets and dynamic inputs.
• Take ownership of the data inputs that feed allocation and packing.
• Validate, normalize, and maintain packing-related datasets.
• 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.

Required qualifications

• Strong programming skills in Python or similar.
• 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 have

• 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

Benefits

• generous equity grant
• full healthcare coverage
• 401k
• unlimited PTO

Before you apply

• This position may require the ability to obtain and maintain a U.S. government security clearance.
• The successful candidate must be able to work in a classified environment when necessary.
• U.S. citizenship is a requirement for all positions at Gallatin.
• Proof of citizenship will be required prior to employment if selected.

About the company

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.