Accenture Federal Services
Cleared AI/ML Engineer
About this role
Accenture Federal Services seeks a cleared AI/ML engineer to develop and deploy machine learning solutions for US federal government clients in defense and national security. The role involves building MLOps frameworks, optimizing production models, and creating custom algorithms that drive mission impact.
What you'll do
- Design and implement MLOps frameworks for various applications and domains
- Deploy, maintain, and optimize machine learning models in production environments
- Develop custom AI/ML algorithms aligned with mission objectives
- Run experiments and fine-tune algorithms to improve model performance
- Collaborate with cross-functional teams to integrate AI/ML solutions into products
- Monitor and improve accuracy and efficiency of deployed models
What they're looking for
- Machine learning and artificial intelligence
- MLOps and model deployment
- Python or similar programming languages
- Data processing and optimization
- Algorithm development and evaluation
- Cross-functional collaboration
- Problem-solving and experimentation
- Security clearance eligibility
Benefits
- Glassdoor Top 100 Best Place to Work recognition
- Professional development through certifications and training
- Hands-on experience with cutting-edge technology
- Collaborative and inclusive work environment
- Opportunity to impact national security missions
- Growth and learning opportunities
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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 developing and deploying MLOps frameworks in production environments. What tools and platforms have you used?
- Walk us through a time when you had to optimize an ML model for performance and accuracy. What metrics did you track and how did you measure success?