AI/ML Engineer — Generative AI Mission Systems

Rackner

USA

AI/ML Engineer — Generative AI Mission Systems Location: Mainly remote within the United States, with onsite collaboration in Laurel, Maryland, typically one day approximately every six weeks for team-wide sprint planning.Clearance: Active final DoD Secret clearance required This position supports a pending contract opportunity and is contingent upon contract award, with an anticipated start in November 2026. Build Applied AI for Secure Mission Software Help turn generative-AI concepts into dependable capabilities used within secure mission-planning and decision-support software. At Rackner, you will integrate large language models, retrieval-augmented generation, agentic AI, prompt-engineering workflows, and inference pipelines into an established software application supporting a high-impact national-security mission. You will work across AI, software engineering, cybersecurity, DevSecOps, and customer technical teams to move capabilities beyond standalone demonstrations and into practical application workflows. This role offers the opportunity to deepen your applied-AI experience, influence how emerging capabilities are designed and evaluated, and contribute to software where re

Requisitos

Active final DoD Secret clearance required This position supports a pending contract opportunity and is contingent upon contract award, with an anticipated start in November 2026. Build Applied AI for Secure Mission Software Help turn generative-AI concepts into dependable capabilities used within secure mission-planning and decision-support software. At Rackner, you will integrate large language models, retrieval-augmented generation, agentic AI, prompt-engineering workflows, and inference pipelines into an established software application supporting a high-impact national-security mission. You will work across AI, software engineering, cybersecurity, DevSecOps, and customer technical teams to move capabilities beyond standalone demonstrations and into practical application workflows. Thi

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