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Principal ML Ops Engineer

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Citizens Bank

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Location:
United States , Charlotte ▼

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

175000.00 - 230000.00 USD / Year
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Job Description:

Principal ML Ops Engineer who will lead the design and operationalization of ML systems on AI/ML platforms such as AWS SageMaker and H2O.ai. This role focuses on building scalable ML systems rather than individual models and includes leadership responsibilities for mentoring and grooming talent in global capability centers (GCC) with potential onshore leadership opportunities. The position also requires hands-on experience with GenAI, including building intelligent agents and exposure to Agentic AI concepts.

Job Responsibility:

  • Lead and mentor engineering teams, including GCC talent development and potential onshore leadership
  • Architect, design, and build ML engineering systems on the CFG ML Platform to accelerate ML pipeline delivery
  • Develop and enhance platform capabilities and frameworks to standardize and automate ML pipeline deployment
  • Implement capabilities such as feature stores, feature tracking, feature serving (real-time and batch), model performance monitoring, model lineage tracking, model health, and model serving and consumption (real-time, batch, event-triggered, near real-time using Kafka)
  • Define processes, research market trends, and implement best practices for ML pipeline development and deployment
  • Collaborate with business teams, data science teams, enterprise architects, and security to uphold ML engineering standards
  • Develop CI/CD pipelines for continuous integration and delivery of ML models
  • Identify and automate ML pipeline and model deployment patterns to streamline workflows
  • Troubleshoot and resolve issues related to ML system performance and deployment
  • Contribute to GenAI initiatives, including building intelligent agents and integrating them into ML Ops workflows
  • Demonstrate exposure to Agentic AI concepts and proof-of-concepts (POCs)

Requirements:

  • 7+ years of experience with Python for scripting ML workflows
  • 5+ years of experience deploying ML pipelines and systems using AWS SageMaker
  • 3+ years of experience developing APIs with Flask, Django, or FastAPI
  • 2+ years of experience with ML frameworks and tools such as scikit-learn, PyTorch, XGBoost, LightGBM, MLflow
  • Solid understanding of the ML lifecycle: model development, training, validation, deployment, and monitoring
  • Solid understanding of CI/CD pipelines for ML workflows using Bitbucket, Jenkins, Nexus
  • Experience with ETL processes for ML pipelines using Spark and Kafka
  • Bachelor’s Degree or equivalent combination of education, training, and experience required

Nice to have:

  • Preferred experience with H2O.ai
  • Preferred experience with containerization using Docker and orchestration using Kubernetes
  • Required exposure to GenAI and Agentic AI concepts, including building or contributing to POCs
What we offer:
  • comprehensive medical, dental and vision coverage
  • retirement benefits
  • maternity/paternity leave
  • flexible work arrangements
  • education reimbursement
  • wellness programs
  • competitive pay
  • opportunity to earn an annual discretionary bonus

Additional Information:

Job Posted:
January 25, 2026

Employment Type:
Fulltime
Work Type:
Hybrid work
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