Description

You will lead the design, deployment, and operationalization of machine learning systems in the cloud.

This role is on-site.

Responsibilities

• Design and manage cloud infrastructure using AWS services including EKS, EC2, SageMaker, Lambda, and S3.
• Automate resource provisioning and configuration using Terraform and Infrastructure as Code practices.
• Implement CI/CD pipelines for ML model deployment via GitHub Actions, Jenkins, or AWS CodePipeline.
• Monitor and optimize ML workflows within Databricks for performance and scalability.
• Develop APIs using FastAPI to serve models, supporting synchronous, asynchronous, and streaming inference.

Required Skills

• 5+ years of experience in ML model lifecycle and deployment best practices.
• Strong expertise in AWS cloud services.
• Proficiency with Terraform and Kubernetes/EKS for container orchestration.
• Hands-on experience with CI/CD tooling.
• Backend development using Python and FastAPI.
• Experience building front-end interfaces with React.
• Familiarity with Databricks for ML workflow monitoring.
• Solid understanding of DevOps tooling and software engineering principles.

Key Skills

Education

Any Graduate