Gallatin
AI Engineer - Allocation and Packing Systems
El Segundo, CA
Sponsorship not specifiedDetected 200 days ago
PythonAlgorithmsMachine LearningData EngineeringA/B TestingCybersecurityLogisticsResearchCommunication
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Cap-exempt (no lottery)0
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Entry-level history0
PERM / green-card track0
Lottery odds40
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About the role
- From factory to foxhole, we operate at the layer where data becomes decisions, and decisions make the advantage.
- 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.
Responsibilities
- Design and implement packing and allocation models for transport assets.
- Implement and tune heuristics or exact approaches for packing and allocation problems.
- Validate, normalize, and maintain packing-related datasets.
- Manage edge cases and incomplete data directly.
- Partner with teams to validate physical executability.
- Validate solutions through scenario testing and operational feedback.
- We build AI systems that determine how logistics decisions are made - not just how they're executed.
- This position may require the ability to obtain and maintain a U.S. government security clearance.
Requirements
- Own data inputs required for allocation and packing, including asset and supply.
- 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.
- Note: Due to the nature of certain government contracts held by this organization, U.S. citizenship is a requirement for all positions at Gallatin. Proof of citizenship will be required prior to employment if selected.
- The successful candidate must be able to work in a classified environment when necessary.
- Proof of citizenship will be required prior to employment if selected.
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 problems.
- Background in operations research, applied math, industrial engineering, or related fields.
- 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.
- 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.
Compensation
- Gallatin offers competitive compensation commensurate with experience.
- Actual compensation may vary based on experience, skills, and location.
- In addition to base salary, we offer a generous equity grant, full healthcare coverage, 401k, unlimited PTO, and the perks of working in a high-caliber, mission-driven environment.
- We comply with the United States Department of Labor's Pay Transparency provision https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_English_unformattedESQA508c.pdf.
Company info
- In addition to base salary, we offer a generous equity grant, full healthcare coverage, 401k, unlimited PTO, and the perks of working in a high-caliber, mission-driven environment.
- At Gallatin, we are rebuilding logistics infrastructure for the national security missions of the United States and allied partners.
Equal opportunity
- Gallatin is an equal opportunity employer.
Visa & Work Authorization
- government security clearance
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This listing is sourced directly from Gallatin's careers page and normalized into a canonical job model.