> Markdown version of [/jobs/ext/3253276-ai-ml-engineer-enablement](https://www.wearedevelopers.com/jobs/ext/3253276-ai-ml-engineer-enablement). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI-ML Engineer (Enablement) - **Company:** MINERVA DEFENSE INC. - **Location:** Dayton, OH, United States (Remote available) - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, CompTIA Security+, Data Governance, DevOps, Web Development, Python (Programming Language), Machine Learning, Metadata Standards, Tensorflow, Azure Machine Learning, Systems Integration, Web Applications, Pytorch, System Availability, Large Language Models, Prompt Engineering, Model Validation, Generative AI, HuggingFace, Machine Learning Operations, Artificial Intelligence Markup Language (AIML) - **Published:** September 21, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=0cfd823b8ae067fa ## About the Role * CompTIA Security+ (DoD 8570 / 8140 IAT Level II baseline) or a globally recognized equivalent. * Bachelor's degree in engineering or related discipline. * 3 or more years of experience as an AI ML Engineer or similar. * Demonstrated experience building and deploying both discriminative (classification, detection) and generative (LLM, GAN, or similar) AI/ML models. * Proficiency in Python and common ML/AI frameworks (e.g., PyTorch, TensorFlow, Hugging Face, LangChain). * Experience with LLM-specific techniques such as retrieval-augmented generation (RAG), prompt engineering, model fine-tuning, and vector databases (e.g., FAISS, Pinecone, or similar). * Experience developing web applications or interfaces for technical/analyst-facing tools * Familiarity with cloud AI/ML services (AWS SageMaker/Bedrock, Azure AI, or equivalent) and MLOps practices for model deployment and monitoring. * Experience working with metadata standards, model cataloging, or data governance practices. * Understanding of data compliance, security, and access-control considerations in a regulated or classified environment. * Strong written and verbal communication skills; comfortable presenting technical findings to both technical and non-technical stakeholders. * U.S. Top Secret Security Clearance. * US Citizenship. Desired Qualifications * U.S. Top Secret / SCI Security Clearance. * Prior experience supporting a defense, intelligence, or other mission-focused federal customer strongly preferred. ## Description This AI ML Enablement Engineer isn't necessarily building the models - they're building the web apps, metadata catalogs, access provisioning/automation, and general support so that the outputs of the AI/ML team are actually usable by the broader NASIC workforce. Background and tools will focus on web application development, systems integration, identity/access automation, DevOps-adjacent work, with enough AI/ML fluency to understand how to integrate and manage that data., * Design, develop, and evaluate discriminative and generative AI/ML models in direct support of NASIC's analytic mission. * Research and report on AI/ML model utilization, availability, and access, as well as data availability and quality for model training and inference. * Build web-based user interfaces that enable analysts and developers to discover, access, and exchange AI/ML-related information across NASIC. * Develop metadata exchange interfaces for AI/ML models and model providers, improving discoverability and interoperability across teams. * Provide hands-on enablement support for AI/ML services - helping analysts and developers adopt and effectively use available models and tooling. * Design and implement an automated process for workforce access provisioning to large language models (LLMs). * Communicate findings, model performance, and access/availability discoveries back to the Product Owner, GTM, and SMEs on a recurring basis. * Support secure, compliant deployment of AI/ML capabilities within a regulated government cloud environment.