> Markdown version of [/jobs/ext/2600258-ai-ml-technical-lead](https://www.wearedevelopers.com/jobs/ext/2600258-ai-ml-technical-lead). 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 Technical Lead - **Company:** Xtreme Inc - **Location:** Fort Lee, VA, United States (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, Microsoft Azure, Monitoring of Systems, Python (Programming Language), Machine Learning, SAP ERP, NumPy, Recommender Systems, Power BI, Standard Sql, Azure Machine Learning, Search Technologies, Test Data, Feature Engineering, Microsoft Power Automate, Azure Data Factory, Deep Learning, Model Validation, SC Clearance, Pandas, Scikit Learn, Information Technology, Machine Learning Operations, Powerapps - **Published:** August 7, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=dfab9a46087175a7 ## About the Role 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. ## Description * 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. ## Related Videos - [Headless by Design: Building Enterprise Systems That Agents Can Actually Use](https://www.wearedevelopers.com/videos/100092-headless-by-design-building-enterprise-systems-that-agents-can-actually-use) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Vectorize all the things! 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