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MLOps Engineer
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MLOps Engineer
Infosys- Posted an hour ago
- Be among the first 10 applicants
Job Description
- SageMaker 2. MLflow 3. Kubeflow 4. Databricks 5. MLOps 6. Model Deployment 7. Model Monitoring 8. Model Retraining 9. Feature Store 10. CI/CD for ML 11. Training Pipelines 12. Inference Pipelines 13. Drift Detection 14. Docker 15. Kubernetes/EKS 16. Terraform 17. CloudFormation 18. AWS Lambda 19. Python Automation
- 5+ yrs DevOps/Cloud/MLOps experience; Python for scripting and automation
- Strong with Jenkins, Git, Docker, EKS troubleshooting
- AWS: SageMaker, Lambda, S3, ECS, IAM, RDS, infra creation
- IaC: CloudFormation (CFT) and Terraform
- MLOps: build/operate ML pipelines deploying to SageMaker, Databricks, or Lambda
More Info
Key Skills
Training Pipelines
Feature Store
MLflow
Kubernetes EKS
Model Retraining
SageMaker
Drift Detection
Model Deployment
Kubeflow
Inference Pipelines
CI CD for ML
About Company
Skills:
SageMaker Unified Studio (SMUS), Managed Workflows for Apache Airflow (MWAA), Infrastructure as Code (IaC), Pyspark, Github, Amazon S3, MLops, AWS CloudFormation, Cloud migration strategies, AWS CDK, AWS Glue Data Catalog, AWS Lake Formation, aws-smus-cicd-cli, GitHub Actions, AWS SageMaker, JWT federation, EMR on EC2 clusters, AWS data and machine learning services, manifest.yaml, OIDC
Skills:
Prometheus, Grafana, Tensorflow, Pytorch, Docker, Terraform, Python, Azure DevOps, AWS, Cloudformation, Sql, Jenkins, Git, Gcp, Spark, Arm, Azure, Kubernetes, Airflow, scikit-learn, MLflow, Feast, Prefect, GitHub Actions, Kubeflow, Bicep, GitLab CI, rbac, Dagster
Skills:
Gcp, Terraform, Docker, Kubernetes, Python
Skills:
Infrastructure-as-Code (IaC), Apache Airflow, Gcp, Docker, Terraform, Azure, Python, AWS, Kubeflow, GitOps, Cloud-native infrastructure, CI/CD
Skills:
Pytorch, Python, Kubernetes, Docker, Dask, DeepSpeed, Airflow, MLflow, Ray.io, TensorRT