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 up-to-date, 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.

📌 MLOPS Engineer (Gurugram)
🏢 Cognizant Softvision
📍 Gurugram