Role description:
The MLOps Support Engineer ensures smooth deployment, monitoring, and maintenance of machine learning models in production environments.
Bridge the gap between data science and IT operations, focusing on operational reliability, automation, and scalability of ML workflows.
The engineer will provide technical support for ML pipelines, troubleshoot issues, and maintain infrastructure for continuous integration and delivery (CI/CD) of ML models.
Responsibilities :
Model Deployment & Integration:
Monitoring & Maintenance
Infrastructure Management
Support & Troubleshooting
Compliance & Security
Qualification and Specialization:
Masters / Bachelors degree –specialization in Machine Learning , IT/Computer Science
• Good communication skills – Collaboration with customer and internal team across shores.
• Familiarity in SQL and other data querying tools
• Knowledge in machine learning models and scheduling
• Strong technical expertise in Python
• Flexibility to work in different shifts
• Knowledge on a cloud technology (preferably GCP and Azure)
• Strong analytical skills for identifying and resolving issues
• Knowledge with data management and monitoring tools
Unique Experience from this Role:
Learning outcomes:
Deep Understanding of ML Lifecycle
Advanced Technical Skills ( Python, devops practices , Cloud, MLOps framework)
Data Engineering & Infrastructure Knowledge
Operational Excellence
Career Growth & Market Value
Soft Skills Development
