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Gallatin

AI Engineer - Allocation and Packing Systems

El Segundo, CAOnsite · United States
FullTime · Engineering
POSTED 1 OCTVERIFIED 1D AGO
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Role
39 days opentrue age
Posted 1 Oct
Payats field
$80k–210kposted
▼ −5% vs market median $152k
$80k$210k
Market p25–p75
$145k–$201k
Gallatin p25–p75
$145kn=5
Los Angeles · n=10 · 365d to 6 Nov
CompanyGallatin →
25open roles
Opened · 30d
+0
Closed · 30d
−0
30d window
Market
3,250open · ML / AI
Opened · 7d
+2267% of open
All ml / ai
6,607open
All tracked boards · live 10 Nov · n=3,250
Python

About Gallatin

At Gallatin, we are rebuilding logistics infrastructure for the national security missions of the United States and allied partners. We build AI systems that determine how logistics decisions are made — not just how they're executed. From factory to foxhole, we operate at the layer where data becomes decisions, and decisions make the advantage.

What You'll Do

Allocation & Packing Modeling

Build, maintain, and implement packing and allocation models for transport assets.

Encode constraints around volume, weight, compatibility, sequencing, and asset usage.

Weigh packing efficiency against runtime and real-world operational constraints.

Algorithm Engineering

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.

Data Ownership & Preparation

Take ownership of the data inputs that feed allocation and packing - asset and supply attributes included.

Validate, normalize, and maintain packing-related datasets.

Manage edge cases and incomplete data directly.

Production Integration

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.

What We’re Looking For

Core Skills

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.

OR Background

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

Systems Thinking

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

Mission and Identity

We are building the system that enables faster, smarter logistics decisions in contested environments, and we're doing it with a team of seasoned entrepreneurs, operators, and technologists who have built and scaled solutions in this space before. We hold ourselves to an extremely high standard. We value clear thinking, direct communication, and the kind of ownership that doesn't stop until something actually works.

Our mission is to create decision advantage when the stakes are the highest. If we succeed, the system doesn't just run; it gets smarter. We're not building AI for its own sake. We're building it because faster, smarter decisions in the most demanding environments on earth can't wait. If you want to work somewhere the stakes are real and the mission is urgent — you'll fit in here.

Why Gallatin?

The logistics infrastructure that supports America's warfighters and humanitarian disaster responders is overdue for transformation, and we are building it. From defense operations to disaster response, we're solving the hardest problems that keep missions moving when it matters most. Join a team where the mission is the point.

Source · GallatinFirst seen 4 NovOriginal ↗