MLOPS Engineer

Cognizant Technology Solutions Corporation; Coimbatore District; Remote; INR 1,500,000 - 2,300,000; Full time

Job summary

Cognizant is hiring a MLOPS Engineer for Pan India. The role focuses on deploying, monitoring, and retraining ML models, with emphasis on scalable deployment pipelines and drift detection. You will work on modern MLOps stacks and contribute to building robust ML workflows across projects.

The ideal candidate has deep Kubernetes experience, strong Python skills, and hands-on ML development. Expect in-person interviews initially with opportunities for remote collaboration where appropriate.

Qualifications

• Strong experience with Kubernetes and MLOps tooling.
• Operationalization of Data Science projects using Kubeflow, SageMaker, GCP AI Platform, or Azure ML.
• Hands-on ML model development with solid ML/AI concepts.
• Proficient in Python for ML and automation; Bash/Unix CLI skills.
• Experience implementing CI/CD/CT pipelines.
• Cloud exposure, preferably AWS.

Responsibilities

• Research and implement MLOps tools and platforms for DS projects.
• Advance MLOps maturity through activity backlog and automation.
• Promote modern, agile, automated DS practices.
• Conduct internal training on MLOps tools and usage.

Skills

Kubernetes

MLOps

Python

CI/CD

AWS Cloud

Tools

Kubeflow

AWS SageMaker

Azure ML Studio

GCP Vertex AI

Terraform

FastAPI

AirFlow

GitHub Actions

AWS CodePipeline

AKS

Databricks

Job description

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.