About leelakrishna
I'm an ML Ops and DevOps Engineer who enjoys building reliable platforms that help software and machine learning teams move faster.Over the last 8 years, I've worked across cloud infrastructure, DevOps, platform engineering, and recently ML Ops. My experience includes building CI/CD pipelines, automating infrastructure with Terraform, deploying applications on Kubernetes, and supporting machine learning models in production on AWS and Azure.In my current role, I work on ML platforms for banking applications where I help automate model training, deployment, monitoring, and infrastructure. Before that, I worked on healthcare platforms using Azure Machine Learning and Databricks, building data pipelines and production-ready ML environments.Earlier in my career, I spent several years designing cloud infrastructure, migrating enterprise workloads to Azure, automating deployments, and improving operational reliability for enterprise applications.I enjoy solving infrastructure problems, automating repetitive work, improving system reliability, and learning new technologies. Recently I've been spending more time exploring AI infrastructure, GPU computing, large language model deployment, and modern platform engineering.Technologies I work with include AWS, Azure, Kubernetes, Docker, Terraform, Python, GitHub Actions, Azure DevOps, Jenkins, MLflow, SageMaker, Azure ML, Databricks, Prometheus, Grafana, and Linux.I'm always interested in connecting with engineers working in Cloud, Platform Engineering, DevOps, AI Infrastructure, and ML Ops.
Key Skills
Experience
Ml Ops Engineer
CurrentWells Fargo
* Working on machine learning infrastructure for fraud detection and transaction monitoring platforms. * Build and maintain end-to-end MLOps pipelines using Amazon SageMaker, EKS, Docker, and Kubernetes. * Automate model training, validation, deployment, and monitoring using Python, Airflow, MLflow, and GitHub Actions. * Deploy scalable inference services on Kubernetes and support real-time and batch prediction workloads. * Build reusable Terraform modules to provision cloud infrastructure across multiple AWS environments. * Implement model monitoring, drift detection, and operational dashboards using CloudWatch and Evidently AI. * Collaborate with data scientists, ML engineers, and application teams to move models from development into production. * Improve deployment reliability, automation, and infrastructure standardization across ML platforms.
Ml Ops Engineer
Mayo Clinic
* Built cloud-based machine learning platforms supporting healthcare analytics and clinical applications. * Developed ML pipelines using Azure Machine Learning, Databricks, and Azure Data Factory. * Automated model training, validation, deployment, and experiment tracking using MLflow and Azure ML. * Built scalable inference services using Docker and Azure Kubernetes Service (AKS). * Created data processing pipelines using PySpark and Databricks for large healthcare datasets. * Managed CI/CD pipelines using Azure DevOps and Infrastructure as Code. * Improved model monitoring, application reliability, and deployment consistency across environments. * Worked closely with data scientists, data engineers, and cloud teams to deliver production-ready ML solutions.
Senior Devops Engineer
Hexagon Ab
* Worked on Azure cloud migration, infrastructure automation, and enterprise platform engineering. * Helped migrate enterprise applications from on-premises infrastructure to Microsoft Azure. * Built reusable infrastructure using Terraform and Bicep. * Managed Azure networking, virtual machines, identity, and security services. * Automated cloud deployments through Azure DevOps pipelines. * Supported Microsoft Entra ID, Microsoft 365 integration, and enterprise identity management. * Implemented monitoring, logging, backup, and disaster recovery solutions for cloud environments. * Worked with development teams to improve deployment automation and platform reliability.
Education
Jawaharlal Nehru Technological University, Kakinada
Bachelor Of Technology
Jawaharlal Nehru University
Bachelors
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Common Questions
What is leelakrishna's expertise?
leelakrishna specializes in MLOps Engineer, with expertise in amazon web services, kubernetes, microsoft azure, ml ops, terraform.
Where is leelakrishna located?
leelakrishna is based in new york, new york, united states.
How much experience does leelakrishna have?
leelakrishna has 9+ years of professional experience.
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