ML ops engineer in Bengaluru at Applisights.com

Job Overview

An MLOps Engineer builds and manages the infrastructure, pipelines, and workflows required to take machine learning models from experimental research into reliable, scalable production environments. [1, 2]

Key Responsibilities

• Model Deployment: Package and deploy machine learning models as scalable APIs, microservices, or batch jobs.

• Pipeline Automation: Build CI/CD pipelines for machine learning to automate model training, testing, and release cycles.

• Monitoring & Maintenance: Track model performance in production to detect data drift, concept drift, or drops in accuracy.

• Collaboration: Work closely with data scientists to turn experimental code (such as Jupyter notebooks) into clean, production-grade applications.

• Infrastructure Management: Manage cloud resources, containerization, and orchestration tools to ensure high availability and security. [1, 2, 3, 4, 5, 6]