Experience: 3–6 years
Location: Bangalore / Hyderabad
About the Role
We are looking for an experienced MLOps/DevOps Engineer to own the infrastructure and automation that takes ML/AI models from development through to production. This role sits at the intersection of machine learning operations and core DevOps engineering, and is responsible for building reliable, automated, and observable pipelines across cloud, containers, and CI/CD.
Key Responsibilities
- Deploy and manage ML/AI models across development, QA, and production environments
- Build and maintain automated pipelines for training, validation, and deployment of ML models
- Design, provision, and manage AWS infrastructure (VPC, EC2, IAM, ALB, S3, RDS, SQS, CloudFront, security groups)
- Administer Linux systems — troubleshoot processes, networking, disk/CPU/memory issues, and write automation scripts
- Build and maintain CI/CD pipelines in Jenkins; troubleshoot failed builds and deployments
- Manage containerized workloads using Docker and Kubernetes (images, deployments, services, ingress, logs, probes)
- Automate configuration management using Ansible
- Provision and manage infrastructure as code using Terraform (variables, state, modules, plan/apply, drift detection)
- Manage source control workflows in Git (branching, merge/rebase, conflict resolution)
- Manage build and artifact pipelines using Maven, npm, and Artifactory
- Set up and maintain monitoring and logging using ELK and CloudWatch; analyze logs, configure alerts, and troubleshoot production issues
Mandatory Skill Areas
- MLOps & ML Model Deployment
- AWS Cloud & Infrastructure
- CI/CD, Containers & Infrastructure Automation
- Linux, Scripting & DevOps Engineering
- Monitoring, Troubleshooting & Production Support
Required Skills
- Hands-on experience deploying ML/AI models to development, QA, or production environments
- Strong working knowledge of AWS core services (VPC, EC2, IAM, ALB, S3, RDS, SQS, CloudFront)
- Proficiency in Linux administration and Bash scripting
- Experience building and maintaining Jenkins CI/CD pipelines
- Solid understanding of Docker and Kubernetes for containerized deployments
- Experience with Ansible for configuration management
- Practical knowledge of Terraform / Infrastructure as Code
- Strong Git skills for version control and collaboration
- Familiarity with Maven, npm, and Artifactory for build and package management
- Experience with monitoring/logging tools (ELK, CloudWatch) and production troubleshooting
