MLOPS Engineer
- Cognizant
- 12 - 14 years
- Bengaluru
- 14 hours ago
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Job Description
Role : MLOps Engineer
Location - AIA Bangalore
Experience- 5 to 1 4years
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 & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Data Platform EngineerEmployement Type: Full timeContact Details:
Company: CognizantLocation(s): Bengaluru
Keyskills: studio continuous integration kubernetes neural networks artificial intelligence sql cloud deep learning automation gcp ml deployment azure databricks cd python github azure machine learning aws sagemaker engineering machine learning framework machine terraform bash aws unix
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