AI/ML Technical Lead for Secure Enterprise Solutions

United States Digital Space LLC; United States; Remote; USD 153,000 - 207,000; Full time

Job summary

GDIT is seeking an AI/ML Technical Lead to drive strategy, architecture, and implementation across CMS programs in the United States. The role emphasizes secure, compliant AI development and leadership across cross-functional teams.

Responsibilities include designing scalable AI/ML models, overseeing MLOps, and embedding governance, security, and risk management into development workflows. A strong background in cloud AI services and production deployments is required.

Qualifications

• 10+ years of AI/ML and related analytics experience.
• Bachelor’s degree in CS, Engineering, Data Science, Mathematics, or related field (Master’s or PhD preferred).
• Hands-on development experience with AI/ML solutions.
• 5+ years deploying AI/ML solutions in production environments, including MLOps practices.
• Proficiency in Python, R, or Java; experience with TensorFlow or PyTorch.

Responsibilities

• Serve as the technical lead for AI/ML strategy, architecture, and implementation across the program.
• Design and deploy scalable AI/ML models to support CMS mission.
• Lead development of predictive analytics, automation, and decision-support systems.
• Ensure integration of AI solutions into secure enterprise environments and comply with cybersecurity standards.
• Mentor engineers and provide technical leadership across cross-functional teams.

Skills

AI/ML strategy

Leadership

MLOps

Security governance

Data governance

Education

Bachelor's degree in CS/Engineering/Data Science

Master’s or PhD preferred

Tools

TensorFlow

PyTorch

AWS SageMaker

Job description

GDIT is seeking an AI/ML Technical Lead to drive strategy, architecture, and implementation across CMS programs in the United States. The role emphasizes secure, compliant AI development and leadership across cross-functional teams.

Responsibilities include designing scalable AI/ML models, overseeing MLOps, and embedding governance, security, and risk management into development workflows. A strong background in cloud AI services and production deployments is required.