Senior MLOps Engineer

About the role

This role is responsible for supporting the development and maintenance of machine learning operations workflows, ensuring reliable deployment, monitoring, and automation of ML models and pipelines. The individual applies foundational ML Ops and DevOps skills to deliver assigned tasks efficiently, contributing to the stability and scalability of production ML systems.

What you'll do

• Maintain and troubleshoot ML pipelines using Python and MLflow, resolving bugs and supporting enhancements based on business requirements
• Support deployment automation of ML models utilizing Jenkins, GitLab CI/CD, and AWS CloudFormation, ensuring consistent and reliable delivery
• Monitor ML workflows and infrastructure using Prometheus and Grafana, identifying and escalating operational issues for timely resolution
• Participate in documentation of ML pipeline enhancements and operational procedures, aligning with CMMi and client standards
• Collaborate within the team to gather requirements and present data using ELK Stack and Fluentd, supporting day-to-day operational needs

What you need

• MLOps
• Machine learning
• Python
• AWS
• Git
• CI/CD
• Any graduate

Good to have

• Jenkins
• Prometheus
• Grafana
• Terraform
• Elasticsearch
• Ansible