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# AI Engineer - SME

- **Company:** Accenture
- **Location:** Chantilly, VA, United States
- **Experience:** Expert
- **Salary:** $109,500.0 - $224,200.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, Computer Programming, Continuous Integration, Data Structures, Distributed Computing Environment, Distributed Systems, Python (Programming Language), Machine Learning, Tensorflow, Azure Machine Learning, Reinforcement Learning, Pytorch, Large Language Models, Generative AI, Containerization, Scikit Learn, Low Latency, Machine Learning Operations, Api Design, Data Pipelines, Microservices
- **Published:** October 16, 2026
- **Apply:** https://www.juju.com/job/1_accentureghi3-4721957006

## About the Role

Join us to drive positive, lasting change that moves missions and the government forward! **Who you'll be:** We are seeking a seasoned AI/ML Engineer to design, develop, and deploy scalable, production-ready AI systems.
This role involves building data pipelines, implementing algorithms in Python, and operationalizing models with MLOps, CI/CD, and containerization.
The role demands optimizing models for performance and ensuring compliance with AI governance and ethical standards. **What you'll do:** + Design, develop, and deploy AI, machine learning, and generative AI systems. + Build and maintain data pipelines for model training, evaluation, and inference. + Implement algorithms using languages such as Python. + Operationalize models utilizing MLOps, CI/CD, and containerization frameworks. + Design and maintain APIs and microservices. + Optimize models for accuracy, latency, and scalability. + Ensure compliance with AI governance, documentation, and ethical standards. **What you need:** + US Citizen with an Active TS/SCI CIP + Bachelor's degree in a relevant field. + 10 years of experience in AI/ML engineering. + Advanced Python programming skills. + Strong understanding of algorithms, data structures, and distributed systems. + Hands-on experience deploying production GenAI/LLM systems, embeddings, and vector databases. + Proficiency
with ML frameworks like PyTorch, TensorFlow, and scikit-learn. + Experience with cloud platforms such as AWS, Azure, or GCP. + Practical experience with MLOps tools like MLflow, Azure ML, or Vertex AI. + Background in NLP, computer vision, or reinforcement learning. **Nice to have:** + Experience in federal, defense, or highly regulated environments. + Knowledge of ethical AI and governance frameworks. + Skills in large-scale optimization, GPU acceleration, or distributed training. + Experience building APIs, microservices, and automated ML workflows.