Posted 1w ago

AI/ML Engineer - TS/SCI + CI Polygraph Required

@ cFocus Software
Washington or Maryland or Virginia
OnsiteFull Time
Responsibilities:developing models, deploying models, optimizing models
Requirements Summary:Active TS/SCI + CI Polygraph clearance; Bachelor's in CS/Math/Data Science (Master's preferred); minimum 4 years AI/ML development; proficiency with TensorFlow, PyTorch, MLOps, and cloud ML platforms.
Technical Tools Mentioned:TensorFlow, PyTorch, AWS SageMaker, Azure ML, Google Vertex AI
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Job Description
cFocus Software seeks an AI/ML Engineer to join our program supporting the Defense Intelligence Agency (DIA). This position is on site in the Washington DC, MD, & VA area. This position requires a TS/SCI + CI Polygraph clearance.
Qualifications:
  • Active TS/SCI + CI Polygraph clearance
  • Bachelor's degree (Master's preferred) in Computer Science, Mathematics, Data Science, or related field with 4-12+ years of experience in AI/ML development
  • Proficient with deep learning frameworks (TensorFlow, PyTorch) and model deployment
  • Experience with model optimization, hyperparameter tuning, and feature engineering
  • Capable of independently developing and deploying production ML models
  • Familiarity with MLOps practices, model monitoring, and Cl/CD for ML
  • Experience with cloud-based ML platforms (AWS SageMaker, Azure ML, Google Vertex AI)
  • Understanding of DIA QAF requirements and model documentation standards
  • Experience with model validation, testing, and performance metrics

Duties:
  • Defines, develops, and delivers machine learning models and AI solutions for intelligence applications.
  • Tests, deploys, and maintains AI systems ensuring compliance with DIA Quality Assurance Framework (QAF) requirements.
  • Optimizes AI models for performance, scalability, efficiency, and accuracy. Manages data flow and infrastructure for effective AI deployment, including data preprocessing and feature engineering.
  • Applies machine learning algorithms to large sets of structured and unstructured data for pattern recognition, target detection and tracking, predictive analytics, and decision support systems.
  • Conducts model validation, bias testing, and performance monitoring to ensure AI systems meet operational and ethical standards.
  • Documents AI/ML methodologies and maintain comprehensive model cards for QAF accreditation.