AI Engineer - Allocation and Packing Systems

Join Gallatin to build AI planning that respects physical reality. This onsite role in El Segundo, CA focuses on packing and allocation models for transport assets, with outputs that plug into resupply and routing workflows. Expect hands-on ownership of data, algorithms, and production-ready logic, backed by competitive compensation, full healthcare coverage, generous equity, and unlimited PTO.

Responsibilities

• Build, maintain, and implement packing and allocation models for transport assets.
• Encode operational constraints including volume, weight, compatibility, sequencing, and asset usage.
• Balance packing efficiency with runtime and real-world operational constraints.
• Develop and refine heuristics or exact methods for packing and allocation problem solving.
• Scale packing solutions across large fleets and dynamic inputs.
• Evaluate tradeoffs between optimality, speed, and explainability.
• Own the 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 outputs are physically executable.
• Validate solutions through 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 challenges.
• Background in operations research, applied math, industrial engineering, or related fields.
• Experience implementing allocation and assignment algorithms such as matching, prioritization, and constraint-based allocation under competing demands.
• Experience modeling and solving packing problems, including bin packing, knapsack, or multidimensional (2D/3D) packing.
• Ability to encode 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.

Bonus Points

• 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.

Tools and Technologies

• Python
• linear programming
• mixed-integer programming
• A/B testing
• causal inference

Compensation and Eligibility

• Salary range: $80,000 - $210,000 per year
• U.S. citizenship required
• This position may require the ability to obtain and maintain a U.S. government security clearance, and you must be able to work in a classified environment when necessary.

Benefits

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