Generative AI Engineer III - Federal Health

This role offers the opportunity to impact federal health initiatives through advanced AI and data solutions. Based onsite in Arlington, VA, you will join Deloitte's Government & Public Services practice, working with a collaborative team, competitive compensation, and a discretionary annual incentive program. The salary range for this position is USD 110,700 to 218,300 per year.

Responsibilities

• Design, develop, validate, and deploy ML and AI solutions for business needs and client engagements.
• Create and maintain data pipelines, model training workflows, and production grade components that power AI enabled products.
• Examine structured and unstructured data to uncover patterns, derive insights, and inform model development and validation.
• Collaborate with engineers, data scientists, product stakeholders, and business teams to translate requirements into practical technical solutions.
• Monitor model and application performance, diagnose issues, and implement improvements to boost accuracy, reliability, and scalability.

Requirements

• Bachelor's degree in computer science, data science, engineering, mathematics, statistics, or another quantitative field.
• Five or more years of professional experience designing, developing, deploying, or supporting ML, AI, or advanced analytics solutions.
• At least three years of experience programming in Python, PySpark, PyTorch, and TensorFlow.
• One or more years of technology consulting experience in the Federal Health space.
• Active certification in one of Python, PySpark, PyTorch, or TensorFlow.
• Ability to travel approximately 20 percent, depending on project and client assignments.
• Authorized to work in the United States without employer sponsorship now or in the future.

Technologies

• Python, PySpark, PyTorch, TensorFlow, Docker, Kubernetes

The Team

Deloitte's Government & Public Services (GPS) practice is designed for impact. Serving federal, state, and local government clients as well as public higher education institutions, our team brings a fresh perspective to help clients anticipate disruption, reimagine the possible, and fulfill their mission promise.

Preferred qualifications

• Master's degree in computer science, data science, engineering, mathematics, statistics, or a quantitative field.
• Ability to obtain and maintain a U.S. government security clearance.
• Two or more years of experience deploying machine learning models into production environments.
• Two or more years of experience with large language models, natural language processing, or generative AI solutions.
• Two or more years of experience using containerization and orchestration tools such as Docker or Kubernetes.
• One or more years of experience supporting model monitoring, governance, or MLOps processes.