About the Role:

• Design and manage scalable AWS cloud infrastructure for MLOps and DevOps workflows, including Kubernetes clusters with Amazon EKS.
• Implement infrastructure as code (IaC) using tools like Terraform, Ansible, or CloudFormation.
• Build and maintain CI/CD pipelines using Jenkins or GitLab CI/CD to automate deployment processes.
• Set up monitoring and logging solutions (e.g., Prometheus, Grafana, ELK Stack, or CloudWatch) to ensure system health and performance.
• Develop scalable pipelines for ML model training, validation, deployment, and monitoring.
• Optimize resource allocation, cost management, and cloud security for AWS services.

About You:

• 6-8 years of hands-on experience with AWS and Kubernetes/EKS, with a bachelor’s degree in IT, Software Engineering, or Computer Science will be preferred.
• Proficient in Python, Linux shell scripting, and tools like Terraform, Ansible, and Jenkins.
• Skilled in monitoring tools such as Prometheus, Grafana, and CloudWatch; knowledge of MLOps tools (Kubeflow, MLflow, Ray) is a plus.
• Experienced in managing cloud networking, security, scaling, and big data platforms like Databricks and Delta tables.
• Familiar with Machine Learning, Generative AI concepts, and tools like PySpark and NumPy.
• AWS (e.g., Solutions Architect) or Kubernetes (e.g., CKA) certifications are a plus.
• Self-motivated with a proven track record of managing production-grade AWS infrastructure and ML pipelines in collaboration with international teams.