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Resume

Machine Learning Support Mlops, LeaD

TECHNICAL SKILLS

  • Data Science Model Life Cycle
  • ML Model Performance Tuning (with SME inputs)
  • ML Model Deployment & Monitorin
  • Docker Containers, Kubernetes & ML Pipelines
  • Model Deployment & Monitoring in Cloud (MLOps)
  • (Azure ML Service/ AWS Sage Maker/ Google AI Platform, IBM)
  • Actual Project Experience in at least one Cloud based ML environment
  • Azure ML Service & Python SDK
  • Python 3.x Programming
  • RESTful APIs for wrapping ML Models / System Integration
  • CI/CD Integration

PROFESSIONAL EXPERIENCE

Confidential

Machine Learning Support (MLOps) Lead

Responsibilities:

  • Gain understanding of Pilot Scope ML models and methodology used.
  • Design and Build the Model Deployment and Monitoring solution for Pilot scope
  • Design and Build production ML pipelines if not available
  • Design and Build deployment and monitoring scripts to be developed
  • Design and Build Model Monitoring scripts & dashboards
  • Regular interaction with business for finalizing the requirements, and model monitoring metrics, reviewing implementation plan etc.
  • Perform Model Deployment in production environment (Azure)
  • Perform Model Refresh
  • Monitor Model Performance
  • Perform Model tuning
  • Tune monitoring scripts and reporting dashboards
  • Analyze and Define Updates to ML Pipeline, Deployment & Monitoring scripts to accommodate any application/data/model changes
  • Model Version & Configuration Management

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