About arun
MLOps Engineer with 3+ years of experience automating ML pipelines, infrastructure provisioning, and CI/CD workflows in AWS and GCP environments. Skilled in integrating ML lifecycle tools like MLflow, Airflow, and FastAPI with DevOps best practices using Terraform, Docker, and Kubernetes (EKS). I’ve deployed containerized ML models with robust monitoring using Prometheus and Grafana, built repeatable infrastructure with Terraform and CloudFormation, and optimized model retraining and versioning through GitHub Actions and MLflow Tracking. Passionate about bridging the gap between data science and production engineering — I specialize in making ML models production-ready: scalable, observable, secure, and efficient. I'm certified in AWS DevOps and GCP Data Engineering, and I’m continuously growing in the MLOps space through hands-on cloud-native ML platform work. Tools I work with: MLflow, DVC, Airflow, FastAPI, Terraform, Docker, Kubernetes, Prometheus, SageMaker, Vertex AI, GitHub Actions. Cloud: AWS (EKS, Lambda, SageMaker), GCP (Vertex AI, Dataflow) Always learning. Always building. Looking to grow in advanced AI infrastructure roles.
Key Skills
Experience
Mlops Engineer
CurrentValuemomentum
Mlops & Devops Engineer
Virtusa
* I work at the intersection of DevOps and MLOps, helping enterprise teams automate, deploy, and monitor scalable ML systems and cloud infrastructure on AWS and GCP. * MLOps Responsibilities: * Designed and deployed CI/CD pipelines using Airflow + GitHub Actions for automated model training and retraining. * Integrated MLflow for model versioning and tracking across experimentation cycles. * Deployed containerized ML models using FastAPI + Docker on AWS EKS with Prometheus/Grafana for real-time monitoring. * Built Terraform modules for SageMaker, Vertex AI, and multi-region AWS infrastructure. * DevOps Responsibilities: * Developed IaC with Terraform and CloudFormation, enabling repeatable and secure provisioning of EC2, S3, Lambda, and VPC. * Automated configuration management using Ansible across Linux-based systems. * Set up observability tools like CloudWatch, ELK Stack, and Prometheus for proactive alerting and diagnostics. * Managed CI/CD for microservices with Jenkins, AWS CodePipeline, and CodeBuild. * Achievements: * Reduced model deployment latency by 40% and provisioning effort by 60%. * Led hybrid ML deployment workflows using GCP Vertex AI for training and AWS EKS for serving. * Ensured high availability and security across multi-account, multi-region AWS setups. * Tools: MLflow, Airflow, FastAPI, Docker, Kubernetes (EKS), Terraform, SageMaker, GitHub Actions, Jenkins, Prometheus, GCP Vertex AI
Education
Lovely Professional University
Bachelors
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Common Questions
What is arun's expertise?
arun specializes in MLOps Engineer, with expertise in airflow, amazon web services, ansible, big query, ci/cd.
Where is arun located?
arun is based in hyderābād, telangana, india.
How much experience does arun have?
arun has 4+ years of professional experience.
How can I contact arun?
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