Cryptocurrency Price Prediction with Sentiment Analysis
Summary
Engineered deep learning models (Informer, Autoformer) to predict BTC/ETH prices using Twitter sentiment analysis.
Highly experienced Site Reliability Engineer with over 4 years of expertise in optimizing cloud infrastructure and implementing robust DevOps best practices. Proven track record of achieving 99.99% uptime for complex enterprise systems, significantly reducing infrastructure costs by 30%, and enhancing deployment efficiency by 60%. Adept in Azure, AWS, Kubernetes, Terraform, and MLOps, with a focus on scalable and resilient cloud solutions.
Senior DevOps Engineer
Istanbul, Istanbul, Türkiye
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Summary
Managed SRE operations for a high-volume travel platform, leading cloud migration efforts and architecting MLOps solutions.
Highlights
Managed SRE operations for a travel platform processing over 1.5B annual transactions, achieving 99.99% uptime through Prometheus/Grafana monitoring and automated incident response.
Led a critical Azure cloud migration for 200+ microservices on OpenShift, reducing infrastructure costs by 30% and deployment time by 60% using Terraform IaC and CI/CD pipelines.
Implemented a comprehensive observability framework with 50+ custom Prometheus metrics and Grafana dashboards, resulting in a 40% decrease in Mean Time To Resolution (MTTR).
Architected an MLOps platform utilizing Kubeflow and MLflow for AI-powered recommendations, streamlining model release cycles from weeks to just 2 days.
Collaborated cross-functionally with 25+ engineers across 4 time zones to establish robust SRE best practices, achieving 95% error budget compliance.
Automated infrastructure provisioning using Azure ARM templates and Ansible, reducing manual tasks by 70% and enhancing operational efficiency.
Cloud Engineer
Istanbul, Istanbul, Türkiye
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Summary
Orchestrated cloud deployments for a supply chain platform, automating infrastructure and modernizing CI/CD pipelines.
Highlights
Orchestrated complex cloud deployments for a supply chain platform serving 50+ enterprise clients, managing Azure infrastructure and reducing associated costs by 25%.
Automated infrastructure provisioning using Terraform and Ansible, drastically cutting deployment time from 4 hours to 30 minutes.
Designed and implemented a robust RBAC framework with 20+ custom roles, reducing access provisioning time by 75% and ensuring SOC2 compliance.
Implemented a comprehensive monitoring stack with Prometheus/Grafana, improving system availability from 97% to 99.5% and reducing MTTR by 40%.
Modernized CI/CD pipelines using Azure DevOps, implementing blue-green deployments to enable zero-downtime releases and enhance system stability.
Site Reliability Engineering
Istanbul, Istanbul, Türkiye
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Summary
Optimized performance for enterprise applications and established SRE practices.
Highlights
Optimized performance for 20+ enterprise applications using Instana APM, reducing P1 incident resolution time from 2 hours to 45 minutes.
Deployed and managed Kubernetes clusters on RedHat OpenShift with auto-scaling and self-healing capabilities, increasing system uptime to 99.5%.
Established and enforced SRE practices, including golden signals monitoring and error budgets, which led to a 40% reduction in Mean Time To Resolution (MTTR).
DevOps Engineer
Istanbul, Istanbul, Türkiye
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Summary
Migrated applications to AWS, developed Terraform modules, and optimized serverless architecture.
Highlights
Successfully migrated over 15 applications from on-premises to AWS (EC2, RDS, S3), resulting in a 30% reduction in monthly costs, saving $8K per month.
Developed comprehensive Terraform modules for AWS infrastructure, automating the deployment of over 50 resources and accelerating development cycles.
Implemented robust CI/CD pipelines using Jenkins and AWS CodeDeploy, achieving a 95% deployment success rate for critical applications.
Optimized serverless architecture leveraging AWS Lambda and API Gateway, significantly improving application response times from 800ms to 200ms.
Teaching Assistant
Istanbul, Istanbul, Türkiye
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Summary
Delivered lab sessions, developed automated grading systems, and mentored teaching assistants.
Highlights
Delivered over 20 lab sessions focused on optimization techniques to 150+ students, achieving a 92% student satisfaction rating.
Developed an automated grading system using Python and VBA, which reduced grading time by 60% and improved efficiency.
Mentored and trained 15+ teaching assistants through structured programs, enhancing their instructional capabilities and team performance.
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Master of Science
Artificial Intelligence
Courses
Focus: Machine Learning
Deep Learning
MLOps
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Bachelor of Science
Computer Science
Grade: 3.2/4.0
Issued By
Microsoft
Azure (AZ-104 Certified), AWS (EC2, RDS, Lambda, S3, SageMaker), Google Cloud Platform.
Kubernetes, Docker, OpenShift, Helm, ArgoCD, Kubeflow.
Terraform, Ansible, Azure ARM Templates, CloudFormation, Pulumi.
Azure DevOps, Jenkins, GitHub Actions, GitLab CI, Tekton.
Prometheus, Grafana, ELK Stack, Datadog, New Relic, Instana APM.
Python, Go, Bash, PowerShell, JavaScript, SQL.
MLflow, Kubeflow, TensorFlow, PyTorch, A/B Testing.
Agile, Scrum, GitOps, SRE Practices, DevSecOps.
Summary
Engineered deep learning models (Informer, Autoformer) to predict BTC/ETH prices using Twitter sentiment analysis.
Summary
Built a decentralized e-commerce platform using React, Node.js, and Solidity smart contracts.