Resume
5.00/5 (Submit Your Rating)
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