Tej Reddy
I’m a DevOps & MLOps engineer with about 5 years of experience building and automating end-to-end ML workflows—covering data pipelines, model training/validation, deployment, and production monitoring.
About
I’m a DevOps & MLOps engineer with about 5 years of experience building and automating end-to-end ML workflows—covering data pipelines, model training/validation, deployment, and production monitoring. I’ve worked across cloud and on-prem environments, with a strong focus on AWS-based infrastructure and reliable CI/CD practices for frequent releases.
I enjoy collaborating with architects, systems, QA, and software teams to improve build and deployment reliability, performance, and automation. In my recent roles, I designed and managed MLOPs platforms (including tools like MLflow and Kubernetes on AWS), implemented containerized deployments, and used monitoring and alerting (CloudWatch, Nagios) to keep production systems healthy.
- 11 years' experience
- Joined October 2026
Skills· 5
Industry experience
- Software & Internet
- Computers & Electronics
- Financial Services
Work experience
Designed and implemented an end-to-end MLOPs platform to train, deploy, and monitor demand forecasting models for pricing and load planning. Improved CI environments, monitored builds, and automated configuration and processes for production releases. Managed AWS infrastructure and automation using tools such as Ansible and Puppet, and supported monitoring using CloudWatch and Nagios. Containerized applications with Docker, deployed to Kubernetes clusters running on AWS, and handled scalable infrastructure management. Worked with Agile teams and coordinated across architects, systems, network, software, and QA to continuously improve build and deployment reliability. Also supported ad hoc environment deployments (using bamboo plans), migrated data between production servers using Bash and Perl scripting, and integrated release notes with JIRA using Perl scripts.
Standardized ML development, deployment, and monitoring across business units by building reproducible training pipelines with MLflow. Provisioned and managed AWS infrastructure resources including VPC, EC2, S3, IAM, EBS, ElasticSearch, Security Groups, Auto Scaling, Lambda, and RDS using CloudFormation, and supported deployment to AWS via EC2/S3/EBS. Supported Agile CI/CD with Atlassian tooling (Jira and Bitbucket), including L3 support. Implemented and maintained CI/CD pipelines using Docker, Jenkins, GitHub, and AWS AMIs, and automated pipelines with Jenkins, Chef, and Terraform. Built automated Tomcat deployment jobs with Jenkins and used Puppet (including custom modules) and Ruby for deployment automation. Managed Git repositories and access strategies, maintained Maven repository setups, and supported RHEL server administration and monitoring.
Built and managed large deployments of Red Hat Linux instances using Chef automation, and provisioned virtual servers with Vagrant/Kitchen on Oracle VM VirtualBox; also provisioned servers in Amazon EC2. Implemented automated build/deployment frameworks and helped create continuous integration systems using Jenkins and Maven. Designed release environments and implemented continuous delivery using Jenkins, Chef, Maven, and Nexus. Managed AWS services such as EC2, S3 (including versioning and lifecycle policies with Glacier), RDS, EBS, and Elastic Load Balancing/Auto Scaling, plus CloudWatch monitoring and alerts. Supported Splunk deployment and troubleshooting across UNIX and Windows platforms, performed release deployments to QA/UAT, and implemented Docker-based CI/CD with GitHub and AWS. Also developed scripting for automation and maintained build/release reliability.
Education
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