AI/ML Engineer SME

About the role

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. Seize your opportunity to make a personal impact as an Artificial Intelligence and Machine Learning Architect Subject Matter Expert 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 Architect SME will work as part of an agile development team to build and support the modernization of enterprise-class software applications.

Responsibilities

• Define, document, and maintain a scalable, modular AI/ML architecture that aligns with enterprise cloud strategy and product requirements for the CMM initiative
• Architect and implement end-to-end AI/ML pipelines including data ingestion, feature engineering, model training, deployment, monitoring, and retraining
• Integrate MLOps best practices for continuous integration, delivery, and lifecycle management of machine learning models
• Ensure multi-tenant and multi-region AI/ML workloads are elastic, highly available, and cost-efficient
• Leverage Infrastructure-as-Code (IaC) tools to provision and manage cloud-based AI/ML infrastructure in accordance with federal compliance and security standards
• Design and support reusable, secure, and performant AI/ML services and APIs to be consumed by enterprise applications
• Conduct model validation and optimization in cloud environments, ensuring responsible AI practices, fairness, and transparency
• Maintain AI/ML architecture documentation and update artifacts per sprint cycles or as changes occur
• Support the inclusion of AI/ML metrics, resource utilization, and performance KPIs in technical dashboards and reports
• Guide teams on the selection and integration of third-party ML tools, frameworks, or SaaS offerings in a secure and compliant manner

Qualifications

• Education: BA/BS or equivalent required; Master's of Arts or Science in related field preferred
• Experience: 15+ years of specialized experience in information systems required
• Experience may be considered in lieu of degree as follows: HS (19+ years), AA/AS (17+ years), BA/BS (15+ years), MA/MS (13+ years), Doctorate Degree/Ph.D. (12+ years)
• Proven success in architecting and deploying ML workflows in cloud environments (AWS SageMaker, Azure ML, GCP Vertex AI)
• Hands-on experience with ML/DL frameworks such as TensorFlow, PyTorch, scikit-learn, XGBoost, or Keras
• Strong programming skills in Python, with experience in containerization (Docker) and orchestration (Kubernetes) for ML workloads
• Experience with MLOps tools (MLflow, Kubeflow, TFX, Airflow) and CI/CD integration for model deployment
• Familiarity with federal data governance, security, and privacy standards, including JISF, NIST 800-53, and FedRAMP
• Proficient in using IaC tools such as Terraform, CDK, or CloudFormation to automate cloud ML infrastructure
• Experience with multi-tenant, distributed systems, and cloud-native architecture patterns

Skills

• Artificial Intelligence (AI)
• Data Analysis
• Data Science

Pay

The likely salary range for this position is $195,240 - $264,148.

Schedule

• Scheduled Weekly Hours: 40
• Travel Required: Less than 10%
• Telecommuting Options: Remote Work Location: Any Location / Remote