AI/ML Engineer at General Dynamics in Any Location
- Company: General Dynamics
- Location: Any Location / Remote
- Salary: $195K – $264K
- Job type: full time
- Workplace: remote
- Posted: 2026-10-14
All open roles at General Dynamics
Job description
Type of Requisition: Regular Clearance Level Must Currently Possess: None Clearance Level Must Be Able to Obtain: None Public Trust/Other Required: BI Full 6C (T4) Job Family: Data Science and Data Engineering Job Qualifications: Skills: Actionable Insights, Data Analysis, Data Analytics Certifications: None Experience: 10 + years of related experience US Citizenship Required: No Job Description: AI/ML ENGINEER SME Own your opportunity to turn data into measurable outcomes for our customers’ most complex challenges. As an AI/ML Engineer SME at GDIT, you’ll power innovation to drive mission impact and grow your expertise to power your career forward. MEANINGFUL WORK AND PERSONAL IMPACT Seize your opportunity to make a personal impact supporting the Case Management Modernization (CMM) Program. GDIT is your place to make meaningful contributions to challenging projects and grow a rewarding career. The AI/ML Engineer will be part of the CMM Data Modernization and Governance team responsible for delivering an integrated data governance, engineering, data platform, reporting, analytics, and Artificial Intelligence (AI)/Machine Learning (ML) capabilities that support operational decision-making and fulfill AO's data and analytics objectives in support of the CMM program. The successful candidate will be responsible for delivering advanced analytics, visualizations, statistical modeling, and AI/ML capabilities; including Generative AI and Agentic AI solutions, predictive models, forecasting, and advanced analytics; that provide data-driven decision-support tools and actionable insights to users and stakeholders of the CMM application. This role provides technical leadership, strategic guidance, and tool recommendations to accelerate product development, and improve decision automation and overall CMM products. The role also oversees design, development, integration, and continuous enhancement advanced analytics and AI/ML capabilities in alignment with strict federal compliance requirements. THE AI/ML ENGINEER WILL EXECUTE THE FOLLOWING RESPONSIBILITIES AI/ML & Advanced Analytics Define and execute AI/ML strategy aligned to CMM modernization objectives. Design, develop, deploy, and maintain ML, predictive, forecasting, Generative AI, Agentic AI, and advanced analytics solutions. Build and tune models using appropriate algorithms, architectures, and data pipelines. Develop LLM-powered applications, RAG pipelines, AI agents, and intelligent automation capabilities. Apply statistical and advanced analytics methods to support data-driven decision-making. Evaluate foundation models, commercial/open-source models, and emerging AI technologies. Create proof-of-concepts and transition successful models to production. Document AI/ML architecture, methodologies, features, and validation results. MLOps / LLMOps / AI Operations Automate model deployment, monitoring, versioning, lineage, and lifecycle management. Build and maintain MLOps/LLMOps pipelines integrated with CI/CD and DevSecOps. Implement automated model training, testing, validation, deployment, rollback, and alerting. Monitor model performance, drift, and degradation; trigger retraining as needed. Maintain reproducible environments and support scalable cloud deployment. Integrate AI/ML pipelines with data engineering and cloud platform services. Responsible AI & AI Governance Ensure compliance with Responsible AI requirements: transparency, fairness, explainability, security, and privacy. Perform bias assessments, model risk evaluations, and bias mitigation strategies. Conduct and document explainability assessments and model interpretability. Lead ATO impact analysis for AI/ML capabilities, support security, privacy, and authorization reviews. Maintain the AI/ML Capability Register, model cards, governance artifacts, and lifecycle documentation. Support AI/ML security assessments, privacy reviews, data classification assessments, and authorization activities. Identify risks such as h
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