AI Engineer

The AI Engineer will design,develop, and deploy machine learning, natural language processing, andgenerative AI solutions supporting the NMMES program at Naval Sea SystemsCommand (NAVSEA) in Norfolk, VA. The role focuses on turning large volumes ofship maintenance, logistics, and readiness data into predictive insights anddecision-support tools that improve fleet availability, reduce unplannedmaintenance, and accelerate work-package planning. The engineer will work directlywith data scientists, software engineers, Navy subject-matter experts, and CACIprogram leadership to move models from prototype to production within an AWSGovCloud environment. This position requires a blend of hands-on MLengineering, MLOps discipline, and comfort operating in a Defense customerenvironment governed by DoD security and accreditation processes. Key Responsibilities

• Design and build supervised, unsupervised, andgenerative AI models (including LLM-based RAG pipelines) against Navymaintenance, supply, and equipment-history datasets.
• Develop end-to-end ML pipelines - data ingestion,feature engineering, training, evaluation, deployment, and monitoring - usingPython and modern ML frameworks (PyTorch, TensorFlow, scikit-learn, HuggingFace).
• Implement MLOps practices in AWS GovCloud usingSageMaker, Bedrock, Step Functions, Lambda, and containerized workloads(ECS/EKS).
• Apply NLP techniques (entity extraction,classification, summarization, semantic search) to unstructured maintenancenarratives, casualty reports (CASREPs), and 3M records.
• Collaborate with data engineers to define schemas,feature stores, and vector databases (OpenSearch, pgvector) that supportproduction inference.
• Establish model governance practices: version controlfor models and datasets, bias and drift monitoring, evaluation harnesses, andhuman-in-the-loop feedback loops.
• Document model design, assumptions, and limitations ina manner suitable for Government review, accreditation, and technical exchangemeetings.
• Support proposal, demonstration, and pilot activitiesas directed by CACI and CDIT Solutions leadership.

• 5+ years of hands-on experience building and deployingML or AI systems in production.
• Expert-level Python, including data-science tooling(pandas, NumPy, scikit-learn) and at least one deep-learning framework (PyTorchor TensorFlow).
• Demonstrated experience with LLMs, prompt engineering,retrieval-augmented generation (RAG), embeddings, and vector search.
• Working knowledge of AWS ML services - SageMaker,Bedrock, Lambda, S3, and IAM - preferably in GovCloud (US).
• Experience deploying containerized workloads (Docker,ECS, or EKS) and building CI/CD pipelines for ML.
• Solid grounding in statistics, model evaluation, andexperimentation methodology.
• Ability to communicate technical concepts clearly tonon-technical Navy and program stakeholders.
• Active DoD Secret clearance at time of hire. Preferred Qualifications
• Prior experience supporting Navy, NAVSEA, or other DoDmaintenance / logistics programs.
• Familiarity with Navy data sources such as NMMES-TR,Maintenance Figure of Merit (MFOM), OARS, or 3M/MDS.
• Experience with responsible-AI frameworks, model cards,and DoD AI ethics principles.
• Exposure to knowledge graphs, ontologies, orgraph-based retrieval.

• TS/SCI clearance. Education Bachelor’s degree in ComputerScience, Data Science, Applied Mathematics, Statistics, or a related technicaldiscipline. Master’s or PhD strongly preferred. Additional relevant experiencemay be substituted for degree requirements consistent with contractlabor-category definitions. Certifications Required

• DoD 8570 / 8140 IAT Level II baseline certification(e.g., Security+ CE) - required within 6 months of hire if not currently held. Preferred
• AWS Certified Machine Learning - Specialty
• AWS Certified Solutions Architect - Associate orProfessional
• Certified Ethical Hacker (CEH) or CISSP