Infosys_ MLOPS Engineer_ PAN India_5+yrs

Glauben Technologies; Pune District, Chennai District, Bengaluru; On-site; INR 2,500,000 - 4,200,000; Full time

Job summary

Glauben Technologies in Pune, India, seeks a seasoned ML/Ops engineer to build scalable machine learning pipelines. You will implement end-to-end ML workflows, manage model deployment, tracking, and versioning, and ensure reliable operations across cloud platforms.

The role requires hands-on experience with Docker, Kubernetes, MLflow/Kubeflow/Airflow, and CI/CD tools such as Jenkins or GitHub Actions. Strong scripting and Linux proficiency are essential for production readiness.

Qualifications

• Strong programming experience in Python.
• Hands-on experience with ML workflows and MLOps.
• Strong understanding of ML lifecycle management.
• Experience with MLflow / Kubeflow / Airflow.
• Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI or Argo CD.
• Strong hands-on experience with Docker and Kubernetes.
• Experience with at least one cloud platform: AWS, Azure or Google Cloud.
• Experience with model deployment and monitoring.
• Knowledge of model versioning, experiment tracking and model registry.
• Experience with REST APIs using FastAPI/Flask.
• Good understanding of Linux and scripting.

Skills

Python

Linux scripting

ML lifecycle management

Model deployment & monitoring

Tools

MLflow

Kubeflow

Airflow

Docker

Kubernetes

AWS

Azure

GCP

FastAPI/Flask

REST APIs

Jenkins

GitHub Actions

GitLab CI

Argo CD

Job description

Role & responsibilities

Mandatory Technical Skills

• Strong programming experience in Python.
• Hands-on experience with Machine Learning workflows and MLOps.
• Strong understanding of ML lifecycle management.
• Experience with MLflow / Kubeflow / Airflow.
• Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI or Argo CD.
• Strong hands-on experience with Docker and Kubernetes.
• Experience with at least one cloud platform:
• AWS
• Microsoft Azure
• Google Cloud Platform
• Experience with model deployment and monitoring.
• Knowledge of model versioning, experiment tracking and model registry.
• Experience with REST APIs using FastAPI/Flask.
• Good understanding of Linux and scripting.