Accenture Federal Services
AI/ML Engineer
About this role
Accenture Federal Services seeks an AI/ML Engineer with 7-20+ years of software engineering experience to develop data-driven solutions for federal government clients. The role combines machine learning model development, statistical analysis, and data preparation using Python, R, and modern AI frameworks in a security-cleared environment.
What you'll do
- Develop and deploy data-driven solutions using Python, R, and programming languages like C++ or Go
- Design, train, and optimize machine learning models using TensorFlow, Scikit-Learn, or SageMaker
- Perform statistical analyses including regression, hypothesis testing, and distribution analysis
- Execute data wrangling and preparation to transform raw datasets for analysis
- Collaborate with cross-functional teams to translate business requirements into actionable insights
What they're looking for
- Python and R programming
- Machine learning frameworks (TensorFlow, Scikit-Learn, SageMaker)
- Agentic AI frameworks (LangGraph, CrewAI, Google ADK)
- Statistical analysis and hypothesis testing
- Data wrangling and preparation
- Data visualization and reporting
- C++, Go, or similar systems programming languages
- Problem-solving and analytical reasoning
Benefits
- Glassdoor Top 100 Best Place to Work recognition
- Professional development through certifications and industry training
- Collaborative and inclusive work environment
- Competitive compensation package
- Opportunity to impact national security and federal missions
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Accenture Federal Services
Accenture Federal Services builds and maintains mission-critical technology solutions for the U.S. federal government, including cloud infrastructure, enterprise systems integrations, and cyber defense tools. The company is hiring DevOps engineers, full-stack developers, SAP specialists, and test engineers to support classified and unclassified federal government projects.
- Website
- accenturefederal.com
Likely interview questions
- Describe your experience with agentic AI frameworks or AI coding agents—which have you used and how did they improve your development workflow?
- Walk us through a machine learning project where you went from raw data to deployed model; what challenges did you face in data preparation?