Machine Learning Production & Deployment Engineer

Lockheed Martin•Manassas, VA

4d•Hybrid

About The Position

The Lockheed Martin Rotary and Mission Systems (RMS) Artificial Intelligence (AI) team is seeking a Machine Learning Production & Deployment Engineer. This position focuses on machine learning production and deployment from data, databases, displays, stack management, Kubernetes & large‑scale infrastructure, and experiment management. The ideal candidate is passionate about a broad range of projects from research & development to prototype development, culminating in deployment of our products to customers. We are on the cutting edge, inserting AI into defense systems, delivered through our AI Factory in partnership with our lines of business. The role is based in Manassas, VA, co‑located with our high‑performance compute cluster, with telecommuting flexibility depending on program needs.

Requirements

Bachelor's or Master's Degree in Software Engineering, Computer Science, Machine Learning, or related STEM degree
1 year of experience required
Experience with AI/ML: disciplines, domain programming languages (e.g. Python, C++, Linux), models, frameworks, and toolsets
DevOps experience including CI/CD pipelines to build, test, deploy
Active security clearance and willing to work onsite with our team in Manassas, VA in our advanced development lab

Nice To Haves

Experience with C/C++, CUDA, NVIDIA libraries, cloud, containers & modern AI tools, or have implemented AI inferencing streaming (e.g. Triton, kserve, etc.)
Experience with production ML and High Performance Compute Development Experience
Strong problem solving mindset: ability to develop create solutions to difficult problems often requiring integration of conflicting and, at times, ambiguous or incomplete data on a fast-paced schedule
Demonstrated ability to effectively communicate complex design information, technical decision and issues to both highly technical and non-technical peers
Ability to build and maintain relationships across organizations, collaborate with others, engage in constructive conflict, and manage interpersonal dynamics
Not afraid to challenge the existing approach to solutions
Comfortable working in a fast paced and dynamic multi-disciplinary environment

Responsibilities

Create innovative machine‑learning solutions and conduct creative ML work that advances AI capabilities.
Develop and containerize software, integrating displays and databases to support end‑to‑end AI pipelines.
Manage high‑performance compute environments, leveraging Kubernetes and large‑scale infrastructure for scalable deployment.
Partner with peer engineering organizations and chief engineer offices to align technical strategies and ensure seamless integration.
Deliver customer‑focused solutions, deploying AI products to the edge and supporting operational use cases.
Collaborate within a close‑knit team, fostering knowledge sharing and continuous improvement.