Hiring For MLOPS Engineer

Glauben Technologies; Pune District, Chennai District, Bengaluru; Hybrid; INR 1,200,000 - 1,800,000; Full time

Job summary

Glauben Technologies seeks an experienced ML engineer to design and implement end-to-end ML pipelines. You will work with Python, Docker/Kubernetes, and modern MLOps tools to deploy and monitor models. The role emphasizes building scalable ML workflows, versioning, and API-based services on cloud platforms such as AWS, Azure, or GCP.

The ideal candidate has hands-on experience with CI/CD and will collaborate across data, software, and infrastructure teams to optimize ML lifecycle performance.

Qualifications

• Proficient in Python with ability to build robust ML pipelines
• Hands-on experience with ML workflows and MLOps practices
• Strong understanding of ML lifecycle management and model governance
• Experience deploying ML models with REST APIs (FastAPI/Flask)
• Hands-on with Docker and Kubernetes container orchestration
• Experience with CI/CD tools (Jenkins, GitHub Actions, GitLab CI, Argo CD)
• Experience with model versioning, experiment tracking and model registry
• Familiarity with ML platforms (MLflow, Kubeflow, Airflow) and cloud providers (AWS/Azure/GCP)
• Strong Linux scripting and automation skills

Skills

Python

ML workflows & MLOps

ML lifecycle management

REST APIs (FastAPI/Flask)

Linux scripting

Tools

Docker

Kubernetes

Jenkins

GitHub Actions

GitLab CI

Argo CD

MLflow

Kubeflow

Airflow

AWS

Microsoft Azure

Google Cloud Platform

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.