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Job Title: DevOps Engineer – AI/ML Infrastructure Location: Meril Healthcare Pvt. Ltd, IITM research park, Chennai, Parent company – Meril (https://www.merillife.com/) . Shift: General shift - Monday to Saturday (9.30 am to 6.00 pm). Summary We are seeking a skilled DevOps Engineer with expertise in managing cloud-based AI/ML infrastructure, automation, CI/CD pipelines, and containerized deployments. The ideal candidate will work on AWS-based AI model deployment , database management , API integrations , and scalable infrastructure for AI inference workloads. Experience in ML model serving (MLflow, TensorFlow Serving, Triton Inference Server, BentoML) and on- prem/cloud DevOps will be highly valued. Key Responsibilities Cloud s Infrastructure Management Manage and optimize cloud infrastructure on AWS (SageMaker, EC2, Lambda, RDS, DynamoDB, S3, CloudFormation) . Design, implement, and maintain highly available, scalable AI/ML model deployment pipelines . Set up Infrastructure as Code (IaC) using Terraform, CloudFormation, or Ansible . CI/CD s Automation Develop and manage CI/CD pipelines using GitLabCI/CD, Jenkins, and AWS CodeBuild . Automate deployment of AI models and applications using Docker, Kubernetes (EKS) . Write automation scripts in Bash, Python, or PowerShell for system tasks. APIs AI Model Deployment Deploy and manage Flask/FastAPI-based APIs for AI inference. Optimize ML model serving using MLflow, TensorFlow Serving, Triton Inference Server, and BentoML . Implement monitoring for AI workloads to ensure inference reliability and performance. Security, Monitoring s Logging Implement AWS security best practices (IAM, VPC,Security Groups, Access Controls) . Monitor infrastructure using Prometheus, Grafana, CloudWatch, or ELK Stack . Set up backup and disaster recovery strategies for databases, storage, and models . Database s Storage Management Maintain and optimize MySQL (RDS) and MongoDB (DynamoDB) databases . Handle structured (RDS) and unstructured (S3, DynamoDB) AI data storage . Improve data synchronization between AI models, applications, and web services . On-Prem s Hybrid Cloud Integration (Optional) Manage on-prem AI workloads with GPU acceleration . Optimize AI workloads across cloud and edge devices . Required Skills and Qualifications 3 to 5 years of experience in DevOps, Cloud Infrastructure, or AI/ML Ops . Expertise in AWS (SageMaker, EC2, Lambda, RDS, DynamoDB, S3) . Experience with Docker s Kubernetes (EKS) for container orchestration. Proficiency in CI/CD tools (Jenkins, GitLab CI/CD, AWS CodeBuild) . Strong scripting skills in Bash, Python, or PowerShell . Knowledge of Linux ecosystem (Ubuntu, RHEL, CentOS) . Hands-on experience with ML model deployment (MLflow, TensorFlow Serving, Triton, BentoML) . Strong understanding of networking, security, and monitoring . Experience with database management (MySQL, PostgreSQL, MongoDB) . Preferred Skills AWS Certified DevOps Engineer, CKA (Kubernetes), or Terraform certification . Experience with hybrid cloud (AWS + on-prem GPU servers) . Knowledge of edge AI deployment and real-time AI inference optimization . Interested , Please share your resume to priyadharshini.sridhar@merillife.com Show more Show less
