MLOps Engineer (AWS, SageMaker, Terraform, DevOps)

About the Company

Infosys is a worldwide frontrunner in digital services and consulting, assisting clients across 46 countries with their digital transformation journeys. With over 30 years of expertise managing global enterprise systems, Infosys drives digital transformation by integrating AI-driven core technologies and delivering agile digital solutions at scale to enhance performance and customer satisfaction. Their continuous learning programs foster the development and sharing of digital skills from their innovation ecosystem.

Role Overview

We are seeking an experienced MLOps Engineer located in Hyderabad to join our team on a full-time basis. The ideal candidate will have between 2 to 5 years of hands-on experience building and managing cloud infrastructure and machine learning model deployments.

Key Responsibilities

• Architect, develop, and maintain CI/CD pipelines leveraging Jenkins, Git, and various automation tools to expedite deployment workflows.
• Deploy, supervise, and sustain Machine Learning models and associated pipelines within AWS SageMaker, Databricks, and AWS Lambda environments.
• Create and administer cloud infrastructure using Infrastructure as Code (IaC) tools including Terraform and AWS CloudFormation templates.
• Containerize machine learning workloads and applications with Docker and deploy them on Kubernetes or Amazon EKS clusters.
• Automate provisioning, configuration, and deployment procedures through Python scripting.
• Manage and optimize the use of AWS services such as ECS, S3, IAM, RDS, Lambda, and SageMaker for reliable operations.
• Diagnose and resolve production issues related to cloud infrastructure, Kubernetes/EKS clusters, and deployment pipelines efficiently.
• Establish monitoring, logging, and alerting frameworks for cloud environments and ML platforms to ensure operational health.
• Collaborate closely with Data Scientists, Machine Learning Engineers, and Development teams to streamline the operationalization of machine learning models.
• Guarantee scalability, security, compliance, and availability for cloud-hosted applications and ML platforms.
• Promote best practices in Infrastructure as Code and drive DevOps automation strategies.
• Support release lifecycle management, environment upkeep, and optimization of cloud resources for performance.

Educational Qualifications and Eligibility

Candidates with educational backgrounds in B.Sc in Any Specialization, B.C.A. in Any Specialization, Any Graduate degree, or B.Tech / B.E. in Any Specialization are eligible to apply.