AI Engineer - SME

Accenture Federal Services•Chantilly, VA
•$109,500 - $224,200

About The Position

Accenture Federal Services is seeking a seasoned AI/ML Engineer to design, develop, and deploy scalable, production-ready AI systems. The role includes building data pipelines, implementing algorithms in Python, and operationalizing models using MLOps, CI/CD, and containerization. The engineer will optimize models for performance and ensure compliance with AI governance and ethical standards. The position supports federal government missions across defense, national security, public safety, civilian, and military health organizations. The company describes a collaborative community that supports employees’ growth through hands-on experience, certifications, and industry training.

Requirements

  • 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 such as PyTorch, TensorFlow, and scikit-learn.
  • Experience with cloud platforms such as AWS, Azure, or GCP.
  • Practical experience with MLOps tools such as MLflow, Azure ML, or Vertex AI.
  • Background in NLP, computer vision, or reinforcement learning.

Nice To Haves

  • 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.

Responsibilities

  • 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 using 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.

Benefits

  • A collaborative and caring community.
  • Hands-on experience, certifications, and industry training.
  • A wide variety of benefits; specific benefits are not listed.
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