AI Engineer-Allocation and Packing Systems

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.

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.

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