AI Engineer - Allocation and Packing Systems

Gallatin is hiring an AI Engineer to build and implement packing and allocation models and algorithms for transport assets. The role focuses on translating optimization outputs into resupply and routing workflows while ensuring generated plans remain physically feasible under operational constraints.

Responsibilities

• Build, maintain, and implement packing and allocation models for transport assets.
• Encode constraints including volume, weight, compatibility, sequencing, and asset usage.
• Balance 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.
• Own data inputs that drive allocation and packing, including asset and supply attributes.
• Validate, normalize, and maintain packing-related datasets.
• Handle 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 using scenario testing and operational feedback.
• Ensure AI-generated plans cannot bypass feasibility or constraint enforcement layers.

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.
• 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.
• Ability to encode capacity, compatibility, priority, and physical constraints within allocation and packing systems.
• Familiarity with optimization techniques including 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.

Technologies

• Python
• Linear programming
• Mixed-integer programming
• A/B testing
• Causal inference

Benefits

• Competitive compensation commensurate with experience
• Generous equity grant
• Full healthcare coverage
• 401k
• Unlimited PTO

Bonus Points

• Experience integrating packing with simulation systems.
• Prior exposure to defense or government planning environments.
• Experience with machine learning models, experimentation (including A/B testing), and causal inference.

Compensation Range

$80,000 - $210,000 USD per year.

Security Clearance / U.S. Government Classified Environment

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.

Citizenship Requirement

U.S. citizenship is required for all positions at Gallatin. Proof of citizenship will be required prior to employment if selected.