AI/ML Technical Lead

• Lead selection and technical refinement of three baseline AI/ML use cases.
• Define mission questions, data requirements, technical baselines, performance metrics, and acceptance criteria.
• Perform hands-on data exploration and feature engineering.
• Develop, train, validate, and comparatively evaluate machine-learning models.
• Conduct error analysis and document model limitations.
• Develop selected GenAI, RAG, forecasting, anomaly-detection, or recommendation capabilities.
• Work with GCSS-Army SMEs to validate business rules and interpret model results.
• Partner with Azure Data/MLOps engineering resources to package, deploy, version, monitor, and sustain models.
• Establish appropriate human-review processes for model outputs affecting operational decisions.
• Develop model cards, evaluation results, release documentation, known limitations, and retraining criteria.
• Integrate analytical outputs into dashboards, Power Apps, APIs, or other operational solutions.
• Participate in demonstrations and production-readiness reviews.

This position requires hands-on technical leadership across AI/ML solutions using CASCOM, GCSS-Army, SAP, and other Army data. The successful candidate must be capable of personally coding, evaluating, deploying, and sustaining models-not simply directing an AI strategy or managing data science teams.

Potential use cases include GenAI/OpenAI, RAG, Copilot, document extraction, anomaly detection, equipment-readiness and maintenance forecasting, fleet automation, recommendation capabilities, and supply forecasting., * Active final Secret clearance.

• 7+ years of data science, machine learning, advanced analytics, or applied AI experience.
• 4+ years developing machine-learning solutions.
• Hands-on production AI/ML development experience.
• Strong Python and SQL skills.
• Experience delivering at least three substantive models or AI capabilities.
• At least one model personally taken from requirements through production or operational deployment.
• Experience with Azure AI/ML services or a comparable cloud environment.
• Ability to explain model evaluation, deployment, monitoring, and retraining.
• Strong experience with pandas, NumPy, scikit-learn, and at least one major ML/deep-learning framework.
• Experience with at least two of the following:
• Forecasting
• Anomaly detection
• Classification
• Recommendation engines
• Optimization
• Document extraction
• NLP, RAG, or GenAI
• Experience establishing measurable model-performance criteria.
• Experience with feature engineering, training, validation/test data, error analysis, explainability, and model documentation.
• Bachelor’s degree in computer science, data science, statistics, mathematics, operations research, engineering, or related discipline, or equivalent specialized experience.

Strongly Preferred

• Azure Machine Learning, Azure OpenAI, Azure AI Search, Microsoft Copilot, or comparable Azure AI services.
• Defense logistics, maintenance, readiness, fleet, supply-chain, acquisition, property, or financial analytics.
• GCSS-Army, SAP ECC, ERP, or maintenance-system data.
• Government-cloud or classified deployment experience.
• Model monitoring, drift detection, bias testing, red teaming, or human-in-the-loop validation.
• Integration of model outputs with Power BI, Power Apps, APIs, or operational applications.
• Experience presenting technical findings to operational users and senior leadership.