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MLOPS Engineer @ Cognizant

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 MLOPS Engineer

Job Description


Role: MLOps Engineer

Experience : 8 yr to 15 yr

Location: PAN India

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.

Job Classification

Industry: IT Services & Consulting
Functional Area / Department: Data Science & Analytics
Role Category: Data Science & Machine Learning
Role: Data Science & Machine Learning - Other
Employement Type: Full time

Contact Details:

Company: Cognizant
Location(s): Hyderabad

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Keyskills:   MLOPS Azure ML Studio MLOps tools

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Cognizant

Company DetailsCognizant Technologies Ltd