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AI​/ML Operations Engineer - TS​/SCI + CI Polygraph

Job in Washington, District of Columbia, 20022, USA
Listing for: cFocus Software Incorporated
Full Time position
Listed on 2026-07-04
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Cloud Computing: Infrastructure & Operations, Data Engineering
Salary/Wage Range or Industry Benchmark: 100000 - 130000 USD Yearly USD 100000.00 130000.00 YEAR
Job Description & How to Apply Below
Position: AI/ML Operations Engineer - TS/SCI + CI Polygraph Required

cFocus Software seeks a AI/ML Operations 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, Data Science, or related field with 4-12+ years of experience
  • Experience with MLOps tools (MLflow, Kubeflow, Sage Maker, Azure ML)
  • Proficient in containerization (Docker, Kubernetes) and orchestration for ML workloads
  • Experience with model deployment, monitoring, and CI/CD for ML
  • Knowledge of ML frameworks (Tensor Flow, PyTorch) and model serving technologies
  • Understanding of data engineering and feature engineering pipelines
  • Experience with cloud ML platforms and infrastructure as code
Duties:
  • Designs, implements, and maintains MLOps infrastructure and pipelines for enterprise AI/ML systems.
  • Manages end-to-end ML lifecycle including model training, deployment, monitoring, and retraining.
  • Implements automated ML pipelines, model versioning, and experiment tracking.
  • Ensures ML systems are scalable, reliable, and performant in production environments.
  • Integrates ML workflows with Dev Sec Ops  practices and maintains compliance with DIA QAF requirements.
  • Monitors model performance, detects drift, and implements automated retraining workflows.
  • Manages ML infrastructure including GPU clusters, feature stores, and model registries.
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