AI/ML SME

Diaconia LLC•Kings Park, VA

1d•$130,000 - $160,000•Hybrid

About The Position

Diaconia is seeking an AI/ML SME to support a federal civilian customer's enterprise data modernization program. This role supports a mission-critical, nationwide case-management and intelligence-analysis platform that integrates enterprise data, analytics, reporting, enterprise search, AI/ML-enabled enrichment, and operational workflows across multiple regions. The AI/ML SME will serve as the analytic team lead for AI/ML initiatives that enrich enterprise data and improve analytical capabilities across mission data holdings. The role will support development, enhancement, training, validation, deployment, and maintenance of AI/ML models, with emphasis on entity extraction, relationship identification, unstructured data processing, model evaluation, model monitoring, and integration of AI/ML outputs into the broader data ecosystem.

Requirements

U.S. Citizenship required.
Active U.S. government Secret clearance or higher required at proposal submission.
Bachelor's degree and 10+ years of related experience required.
Four additional years of relevant experience may be substituted in lieu of a Bachelor's degree.
A Master's degree or higher may reduce the required experience by two years.
10+ years of overall related professional experience in data science, analytics, AI/ML, data engineering, enterprise data, or mission analytics environments.
5+ years of in-depth experience with at least one analytical or statistical language, such as Python, R, or SQL.
At least 2 years of experience with custom machine learning and AI model training, including supervised and unsupervised learning.
At least 2 years of Natural Language Processing expertise focused on unstructured data.
3+ years of experience with SQL database development, SQL coding, or SQL-based analytical work.
2+ years of experience with data visualization tools.
2+ years of experience manipulating unstructured data.
Experience developing, testing, validating, deploying, documenting, and maintaining AI/ML models.
Experience supporting enterprise data, reporting, search, O&M, modernization, or cloud-enabled analytics environments.
Must be able to be ON SITE 3 days or as required by the client.
Occasional OCONUS travel may be required.

Nice To Haves

Educational background in Data Science or a related technical field.
Experience with federal civilian, law enforcement, investigative, intelligence, or sensitive mission data.
Experience with entity extraction, entity resolution, relationship analysis, or enrichment of large unstructured datasets.
Experience integrating model outputs into enterprise search, reporting, data warehouse, or analytics platforms.
Experience with model monitoring, retraining, performance drift detection, and responsible AI validation practices.
Experience supporting Agile Scrum delivery and documenting work in Azure DevOps or similar tools.

Responsibilities

Serve as the AI/ML subject matter expert and analytic team lead for data science initiatives.
Lead analytic modernization efforts across enterprise data and mission analytics environments.
Provide technical and management leadership on major tasks and technology assignments.
Establish goals and plans that meet project objectives; supervise others as needed.
Evaluate enterprise data holdings and identify data sources suitable for AI/ML model development, enrichment, and mission analytics.
Develop, train, test, tune, validate, and deploy machine learning and AI models aligned to approved business use cases.
Support supervised and unsupervised learning, natural language processing, entity extraction, relationship identification, and unstructured data manipulation.
Design and implement ETL processes to extract, clean, standardize, and prepare source data for model training and deployment.
Support development and delivery of high-quality data systems, reports, analytical products, and features.
Support O&M for existing data systems, including enterprise data warehouse integrations, enterprise reporting, enterprise search/OpenSearch, and AI/ML-enabled enrichment.
Support enterprise reporting via Power BI dashboards and data calls.
Support enterprise search/OpenSearch capabilities, APIs, and business intelligence functions where AI/ML integration or data enrichment is required.
Document model assumptions, data inputs, training parameters, validation results, deployment configuration, and reproducibility steps.
Conduct independent validation of model outputs for accuracy, stability, and bias detection.
Package and deploy validated models to designated test or production environments.
Configure application interfaces, APIs, or automation pipelines required for model operations.
Establish model monitoring and retraining mechanisms to detect performance drift.
Prepare AI business case summaries, leadership briefings, and technical documentation explaining model purpose, value proposition, expected outcomes, and integration opportunities.
Coordinate with data engineering, reporting, search, cloud, security, and product owner teams to integrate AI/ML capabilities into the broader enterprise data ecosystem.
Support modernization across cloud and non-cloud technology stacks.