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Senior+
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Full-time
bachelor degree, postgraduate degree
Posted 46d ago
~40 hrs/week
Responsibilities
The AI Engineer will design, develop, and deploy machine learning and generative AI solutions to support ship maintenance and logistics data analysis. They will collaborate with cross-functional teams to move models from prototype to production within a secure AWS GovCloud environment.
Requirements
Candidates must have at least 5 years of experience in building and deploying production-level AI systems and possess an active DoD Secret clearance. Proficiency in Python, deep learning frameworks, and MLOps practices is required, along with a relevant bachelor's degree.
Full job description
The AI Engineer will design,
develop, and deploy machine learning, natural language processing, and
generative AI solutions supporting the NMMES program at Naval Sea Systems
Command (NAVSEA) in Norfolk, VA. The role focuses on turning large volumes of
ship maintenance, logistics, and readiness data into predictive insights and
decision-support tools that improve fleet availability, reduce unplanned
maintenance, and accelerate work-package planning.
The engineer will work directly
with data scientists, software engineers, Navy subject-matter experts, and CACI
program leadership to move models from prototype to production within an AWS
GovCloud environment. This position requires a blend of hands-on ML
engineering, MLOps discipline, and comfort operating in a Defense customer
environment governed by DoD security and accreditation processes.
Key Responsibilities
•Design and build supervised, unsupervised, and
generative AI models (including LLM-based RAG pipelines) against Navy
maintenance, supply, and equipment-history datasets.
•Develop end-to-end ML pipelines — data ingestion,
feature engineering, training, evaluation, deployment, and monitoring — using
Python and modern ML frameworks (PyTorch, TensorFlow, scikit-learn, Hugging
Face).
•Implement MLOps practices in AWS GovCloud using
SageMaker, Bedrock, Step Functions, Lambda, and containerized workloads
(ECS/EKS).
•Apply NLP techniques (entity extraction,
classification, summarization, semantic search) to unstructured maintenance
narratives, casualty reports (CASREPs), and 3M records.
•Collaborate with data engineers to define schemas,
feature stores, and vector databases (OpenSearch, pgvector) that support
production inference.
•Establish model governance practices: version control
for models and datasets, bias and drift monitoring, evaluation harnesses, and
human-in-the-loop feedback loops.
•Document model design, assumptions, and limitations in
a manner suitable for Government review, accreditation, and technical exchange
meetings.
•Support proposal, demonstration, and pilot activities
as directed by CACI and CDIT Solutions leadership.
Required Qualifications
•5+ years of hands-on experience building and deploying
ML or AI systems in production.
•Expert-level Python, including data-science tooling
(pandas, NumPy, scikit-learn) and at least one deep-learning framework (PyTorch
or 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, and
experimentation methodology.
•Ability to communicate technical concepts clearly to
non-technical Navy and program stakeholders.
•Active DoD Secret clearance at time of hire.
Preferred Qualifications
•Prior experience supporting Navy, NAVSEA, or other DoD
maintenance / 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, or
graph-based retrieval.
•TS/SCI clearance.
Education
Bachelor’s degree in Computer
Science, Data Science, Applied Mathematics, Statistics, or a related technical
discipline. Master’s or PhD strongly preferred. Additional relevant experience
may be substituted for degree requirements consistent with contract
labor-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 or
Professional
•Certified Ethical Hacker (CEH) or CISSP
Related keywords
AI EngineerMachine LearningNatural Language ProcessingGenerative AINMMESNAVSEAAWS GovCloudMLOpsPythonPyTorchTensorFlowScikit-learnHugging FaceSageMakerBedrockDocker
How many Engineering jobs are open in Norfolk, VA right now?
There are currently 508 open engineering positions in Norfolk, VA listed on Clera. New openings are added daily as companies post roles.
Which companies are hiring for Engineering roles in Norfolk, VA?
Companies currently hiring include Amentum, Valkyrie Enterprises, INDUS Technology, Inc., Booz Allen Hamilton, CACI International Inc, among others. Browse the listings above to see every active employer.
Are there remote or hybrid Engineering jobs in Norfolk, VA?
Yes — 42 of the 508 open engineering positions offer remote or hybrid work (8 remote, 34 hybrid).
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