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Years of experience: 6 - 9 years

Locations: Indore, Noida, Gurgaon, Pune, Bangalore.

Job Description:

POSIT Workbench: Deploy/Manage/Maintain/ Posit Workbench, Connect, and Package Manager on on prem, Kubernetes or cloud-based environments (Azure, AWS, GCP) and provide services like Jupyter Notebook, Jupyter-Lab, Jupyter-Hub, Vscode, R-Studio.

CDP/CDH Big data Admin: integration of CDP tools like hdfs, hive, impala, Spark, Pyspark, spark3.x , Pyspark3.x with IDE platform.

MLOps & Model Deployment: Implement scalable and reliable ML model deployment strategies (batch & real-time inference). working experience on setting up , MSAAS, MLFLow, H2o.ai mandetory.

Kubernetes & Containers: working experience on setting up containerized applications on OpenShift ( mandatory ). Manage Kubernetes clusters, ensuring high availability, autoscaling, and security for ML workloads.

Monitoring & Logging: Implement observability tools like Splunk( mandatory), Prometheus, Grafana, ELK, OpenTelemetry for tracking ML job performance and system health.

Collaboration & Support: Work with Data Scientists & ML Engineers to optimize model performance, troubleshoot issues, and improve ML pipelines.

Security & Compliance: Ensure security best practices, role-based access control (RBAC), and compliance for ML workloads

Good to have skills

CI/CD Pipelines: Automate data science workflows, including model training, testing, and deployment using CI/CD tools like Jenkins, ArgoCD, or GitHub Actions.

Application Security: Integration of SSO authentication for Posit Workbench, and Package Manager, using an use OAuth, SAML, or LDAP with identity providers like Azure AD, Okta, Keycloak, or Ping Identity.

Infrastructure as Code (IaC): Use Terraform, Helm, and Ansible to provision and manage cloud-based ML infrastructure.

Cloud & Storage Management: Optimize cloud compute/storage resources (Azure/AWS/GCP) for AI/ML workloads.