Devops Engineer Mlops

Name: Raghavendra Yerramsetty

Email: ****************@*****.***

Mobile:+1-872-***-****

DeVops Engineer (MLOps Engineer)

Professional Summary:

● 5+ years of experience as a DevOps Engineer, specializing in automating, deploying, and managing scalable, high-availability systems using a wide range of AWS Cloud services to enhance operational efficiency and reduce downtime.

● Here are the list of certifications I have now:

AWS DevOps Engineer - Professional

Google Cloud Engineer - Associate

● Proficient in writing Shell scripts, Python, and other scripting languages to programmatically automate workflows, manage infrastructure, and orchestrate complex deployments.

● Proficient in building and managing Infrastructure as Code (IaC) with Terraform, enabling consistent, efficient, and automated provisioning of AWS resources across multiple environments.

● Expertise in designing and implementing CI/CD pipelines using AWS CodePipeline, CodeBuild, CodeDeploy, CodeCommit, and CodeStar, ensuring seamless integration and rapid delivery of applications.

● Experienced in managing compute services like Amazon EC2, Amazon ECS, Amazon EKS, AWS Lambda, and AWS Elastic Beanstalk, supporting diverse workloads, including containerized and serverless architectures.

● Hands-on experience with AWS CloudFormation and AWS OpsWorks, standardizing and automating infrastructure setup for predictable and scalable deployments.

● Proficient in using monitoring and auditing tools such as Amazon CloudWatch, AWS Config, and AWS CloudTrailto ensure compliance, operational visibility, and proactive issue resolution.

● Adept at implementing logging and distributed tracing solutions with AWS X-Ray and CloudWatch Logs, optimizing application performance and simplifying troubleshooting.

● Strong understanding of networking and security configurations, including Amazon VPC, AWS IAM, AWS Secrets Manager, and Amazon S3, to ensure secure and reliable infrastructure.

● Expertise in container orchestration and microservices deployment using Amazon ECS, EKS, and ECR, delivering scalable, reliable, and efficient solutions.

● Skilled in creating automation workflows for system maintenance and operational tasks using AWS Systems Manager and scripting tools, ensuring efficient management of large-scale environments.

● Adept at building fault-tolerant and resilient architectures, integrating disaster recovery plans, and ensuring uptime through proactive monitoring and infrastructure management.

● Passionate about fostering collaboration between development and operations teams to drive efficiency, reduce deployment times, and deliver high-quality solutions. Name: Raghavendra Yerramsetty

Email: ****************@*****.***

Mobile:+1-872-***-****

DeVops Engineer (MLOps Engineer)

Client: REGENERON - NY Sep 2023 - Present

Role: DevOps Engineer (MLOps Engineer)

Project Overview:

At Regeneron, as a DevOps/MLOps Engineer, I spearheaded the design and implementation of scalable and compliant infrastructure to support advanced machine learning workflows and healthcare applications. My role focused on building end-to-end ML pipelines with Kubeflow, deploying containerized and serverless solutions using Docker, Kubernetes, and AWS ECS/EKS, and automating CI/CD processes to ensure seamless integration and deployment. I also migrated legacy ML systems to AWS SageMaker, optimized cloud resources with Terraform and Puppet, and implemented robust monitoring and security frameworks to maintain HIPAA compliance while driving cost efficiency and operational excellence. Responsibilites:

● Designed and built end-to-end machine learning pipelines leveraging Kubeflow, automating workflows and reducing deployment times by 35% through optimized task orchestration and resource allocation.

● Deployed ML models in production using Docker and Kubernetes, establishing scalable and fault-tolerant containerized environments for real-time inference workloads.

● Engineered robust CI/CD pipelines using Jenkins and GitHub Actions to automate model integration, testing, and deployment, accelerating development cycles and minimizing downtime.

● Implemented advanced monitoring and logging systems with Prometheus, Grafana, and custom metrics exporters, ensuring real-time visibility into model performance and proactive issue detection.

● Collaborated extensively with data scientists and analysts to fine-tune ML models, leveraging tools like DVC and Git to standardize model versioning, improve reproducibility, and facilitate cross-functional collaboration.

● Led the migration of legacy machine learning workflows to AWS SageMaker, optimizing training efficiency by 40% and introducing features like hyperparameter tuning and distributed training.

● Built and deployed containerized healthcare applications using AWS ECS and EKS, reducing infrastructure costs by implementing auto-scaling policies while maintaining compliance with HIPAA standards.

Name: Raghavendra Yerramsetty

Email: ****************@*****.***

Mobile:+1-872-***-****

DeVops Engineer (MLOps Engineer)

● Developed advanced Dockerfiles, Puppet scripts, and Terraform configurations to automate the provisioning of secure, compliant infrastructure across development, staging, and production environments.

● Orchestrated cloud migration initiatives, utilizing AWS services like S3, IAM, RDS, and CloudWatch to modernize legacy systems and enhance scalability.

● Enhanced security and compliance by implementing IAM role-based access control, secret management with AWS Secrets Manager, and encryption at rest using KMS.

● Devised disaster recovery strategies, including automated model backups to Amazon S3 and multi-region failover architectures, ensuring system reliability and data integrity.

● Automated routine operational tasks with AWS Lambda and Systems Manager, enabling self-healing infrastructure and reducing manual intervention by 50%.

● Established comprehensive observability frameworks using AWS CloudWatch, AWS X-Ray, and OpenTelemetry, providing insights into system bottlenecks and improving response times.

● Spearheaded initiatives to integrate GitOps workflows, ensuring declarative and automated configuration management, minimizing drift, and improving deployment consistency.

● Implemented cost optimization strategies by analyzing workload patterns, optimizing resource usage, and leveraging AWS Savings Plans, reducing cloud expenses by 20%. Client: Infor Pvt Ltd, Hyd, IND May 2019- Dec 2022 Role: DevOps Engineer

Project Overview:

As a DevOps Engineer at Infor India Pvt LTD, I automated deployments, streamlined CI/CD pipelines, and migrated legacy systems to AWS, enhancing scalability and reducing costs. Leveraging tools like Ansible, Terraform, and Docker, I optimized infrastructure, ensured compliance, and improved efficiency for sensitive healthcare applications. Responsibilites:

● Automated application deployments using Ansible, resulting in a 30% improvement in deployment speed and enhanced system reliability across multiple environments.

● Designed and managed robust CI/CD pipelines with Terraform and GitHub Actions, enabling seamless software delivery while reducing deployment errors and improving collaboration across development and operations teams. Name: Raghavendra Yerramsetty

Email: ****************@*****.***

Mobile:+1-872-***-****

DeVops Engineer (MLOps Engineer)

● Optimized MySQL databases by implementing secure configurations, performance tuning, and backup strategies, ensuring the protection and reliability of sensitive healthcare data.

● Streamlined application containerization using AWS ECS, leading to a 25% reduction in infrastructure costs while improving scalability and operational efficiency.

● Architected and deployed scalable microservices, enabling frequent, reliable releases and improving system resilience to handle dynamic workloads.

● Created and maintained Dockerfiles, Puppet scripts, and Terraform configurations, ensuring consistent and compliant provisioning of infrastructure across development, staging, and production environments.

● Led the migration of on-premise systems to AWS Cloud, leveraging services like ECS, S3, and IAM, which modernized infrastructure, enhanced system scalability, and reduced overall operational costs.

● Established comprehensive monitoring and logging solutions using Prometheus, AWS CloudWatch, and custom alerting mechanisms, improving system observability and minimizing downtime during incidents.

● Enhanced application security by implementing AWS Secrets Manager for secure storage of sensitive information and configuring fine-grained IAM policies to ensure least-privilege access control.

● Automated routine maintenance and operational workflows using AWS Systems Manager, improving efficiency by reducing manual interventions and enabling a more proactive approach to system management.

● Standardized and modularized infrastructure provisioning using Terraform, which reduced deployment times for new environments and minimized configuration drift.

● Integrated automated testing and code quality checks into CI/CD pipelines, ensuring higher reliability and stability for production deployments.

● Introduced GitOps practices, leveraging declarative infrastructure management to ensure consistent deployments, minimize errors, and improve system recoverability.

● Orchestrated containerized applications using Kubernetes, enabling auto-scaling, load balancing, and fault tolerance to maintain high availability during peak traffic periods.

● Conducted regular performance and security audits, proactively identifying bottlenecks and vulnerabilities to maintain optimal system performance and compliance with industry regulations.

● Provided hands-on support for DevOps initiatives, collaborating with cross-functional teams to drive automation, improve system reliability, and align processes with organizational goals.

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