Infrastructure AI/ML Engineer
Tasks
- Define and optimize distributed computing pipelines
- Design cloud and on prem infrastructure for AI and data intensive applications
- Develop and maintain MLOps and DevOps platforms for model lifecycle
- Enable efficient use of specialized hardware accelerators GPU and TPU
- Implement CI CD monitoring and retraining workflows
- Integrate AI platforms into enterprise IT and cloud ecosystems
- Manage clusters containers and orchestration with Kubernetes and OpenShift
- Monitor AI solution performance in production ensure scalability resilience and security
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Apache Spark | Azure DevOps | Bash | CI/CD | Cloud platform | Cloudera | Dask | Databricks | DevOps | Docker | ELK | Google Cloud | Google Cloud Platform | Grafana | Jenkins | Kubeflow | Kubernetes | MLOps | MLflow | Microsoft Azure | OpenShift | Prometheus | Python | Ray
Education
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