Geo Antony

• I Architected and implemented scalable solutions across multiple startups and enterprises • Projects included a large variety, including mission-critical infrastructure, automation and configuration management • I have implemented CI / CD pipelines and managed systems that handle high request volumes, including DevOps, MLOps and SRE • My contributions included designing tech stack, hands-on development, code reviews and maintain technical standards • I provided strategic technical leadership, mentor development teams and create technology roadmap planning

As CTO of Optimitz, an early-stage startup, I’m spearheading the technical foundation for a pioneering self-improvement app set to launch its first version in May 2025. Our mission is to blend AI to redefine personal growth, empowering users to build better habits, boost self-awareness, and unlock their full potential. My work focuses on: 🤖 Developing AI-powered tools for personalized insights. 🍃 Integrating food consumption, nutrition, physical & mental excercise,habits into a single unified platform. 📱Currently developing IOS and android application to run the optimitz platform.

🌍 Built a geo-distribution framework for any application such as Kubernetes & OpenStack—scalable, resilient, no code changes needed 🔗 Designed a P2P architecture with CouchDB for geo-distributed systems 🛠️ Created a modular SOA with REST APIs for flexibility ✅ Tested under high-transaction, multi-region scenarios ⚙️ Automated provisioning with Ansible & Terraform, cutting setup time 👥 Led 2 engineers to develop it in Golang 💻 Tech: Kubernetes, Golang, CouchDB, Ansible, Terraform, Git, Docker, Cloud, Edge

🌐 Pioneered a novel geo-distribution method for apps (e-commerce, text editors, cloud tools), boosting scalability and adaptability without code changes. 🔄 Crafted a reusable, app-agnostic platform. 🗂️ Introduced a sharding-based collaboration model to tackle replication challenges across geo-distributed resources. ⏳ Developed an innovative consistency approach—beyond RAFT, Paxos, or CRDT—for external synchronization. 🔗 Devised a dependency management system for seamless Cloud-to-Edge (CDN) distribution. 💡 Merged Object-Oriented and Aspect programming for flexible, tailored geo-distribution strategies. 👨‍💼 Oversaw the project, designing the tech stack, leading the team, and reviewing code.

🤖 Built a scalable MLOps platform for computer vision, powered by OpenCV, OpenVINO, PyTorch, and TensorFlow for versatile model support. 📹 Set up real-time video streaming pipelines with Kafka, enabling smooth data ingestion and inference across cloud and edge (bare metal). 💾 Managed storage with MinIO, MongoDB, and Redis for indexing. 🚀 Deployed flexible model-serving APIs on Kubernetes, integrating TF Serving, OpenVINO, and Flask for client adaptability. ⚙️ Automated CI/CD via Ansible and GitHub Actions, with Prometheus and Grafana for robust monitoring. 🌐 Linked components across locations using Istio and Consul service meshes, coordinating multi-container model training.

🤖 Crafted an MLOps platform for data scientists, weaving data ingestion and model orchestration with Kubeflow and Airflow. 🔗 Focused mainly on Azure Cloud and Bare metal Infrastructure. ⚙️ Engineered a custom training and hyperparameter tuning system using Katib, Kubernetes, and OpenFaaS for fast parallel processing. 🚀 Rolled out a resilient, high-availability serving setup on Kubernetes, exposing models via PyTorch and TF Serving. 🔗 Tied pipeline stages together with GitLab, Kubeflow, Kafka, Hadoop, and Spark. 📊 Boosted visibility and error tracking with ELK stack (Elasticsearch, Logstash, Kibana) on Kubernetes. ☁️ Spanned infrastructure across bare metal, Azure, and Google Cloud. 🏆 Earned “Employee of the Year” for a high-performance MLOps pipeline that slashed latency and supercharged deployment reliability.