MLOPS Engineer

Cognizant; Chennai District; On-site; INR 2,000,000 - 4,200,000; Full time

Job summary

Cognizant is seeking an experienced MLOPS Engineer to advance deployment, monitoring, and retraining pipelines for ML projects across the enterprise.

You will drive MLOps maturity, implement automation, and conduct internal trainings to showcase the value of modern ML pipelines and observability. Strong cloud, Python, and Kubernetes skills are essential, with in-person interview expectations across India.

Qualifications

• Hands-on experience in ML model development.
• Proficiency with Kubernetes and CI/CD/CT pipelines.
• Operationalization of Data Science projects (MLOps) using frameworks like Kubeflow or SageMaker.
• Strong Python skills for ML and automation tasks; Bash/Unix proficiency.
• Experience with cloud platforms (preferably AWS).

Responsibilities

• Research and implement MLOps tools, frameworks and platforms for Data Science projects.
• Raise MLOps maturity in the organization through backlog activities.
• Introduce modern, automated approach to Data Science.
• Conduct internal training and presentations on MLOps tools.

Skills

Kubernetes expertise

Python for ML & automation

CI/CD pipelines

Unix Bash

Tools

AWS SageMaker

Azure ML Studio

GCP Vertex AI

PySpark

Azure Databricks

MLFlow

KubeFlow

AirFlow

GitHub Actions

AWS CodePipeline

Kubernetes

AKS

Terraform

FastAPI

Job description

• MLFlow, KubeFlow, AirFlow, Github Actions, AWS CodePipeline

Role: MLOPS Engineer

Location: Pan India

Experience: 6 to 15 Years

Notice Period : Immediate to 90 days

Mode of Interview : In-Person

Key Words -Skillset

• AWS SageMaker, Azure ML Studio, GCP Vertex AI
• PySpark, Azure Databricks
• MLFlow, KubeFlow, AirFlow, Github Actions, AWS CodePipeline
• Kubernetes, AKS, Terraform, Fast API

Responsibilities

• Model Deployment, Model Monitoring, Model Retraining
• Deployment pipeline, Inference pipeline, Monitoring pipeline, Retraining pipeline
• Drift Detection, Data Drift, Model Drift
• Experiment Tracking
• MLOps Architecture
• REST API publishing

Job Responsibilities

• Research and implement MLOps tools, frameworks and platforms for our Data Science projects.
• Work on a backlog of activities to raise MLOps maturity in the organization.
• Proactively introduce a modern, agile and automated approach to Data Science.
• Conduct internal training and presentations about MLOps tools’ benefits and usage.

Required Experience And Qualifications

• Wide experience with Kubernetes.
• Experience in operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g. Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, DKube).
• Good understanding of ML and AI concepts. Hands-on experience in ML model development.
• Proficiency in Python used both for ML and automation tasks. Good knowledge of Bash and Unix command line toolkit.
• Experience in CI/CD/CT pipelines implementation.
• Experience with cloud platforms - preferably AWS - would be an advantage.