About Me
- Cloud-Native AI Development & Inference — Design and build end-to-end AI/ML solutions with production-grade MLOps pipelines. Expert in model training, deployment, monitoring, RAG systems, fine-tuning foundation and open-weight models, and scalable, low-latency inference serving.
- Cloud Infrastructure & Solution Design — Certified in AWS (SAA) and Kubernetes (CKA). Architect scalable, cloud-native ML platforms and complete solutions combining AI/ML with robust infrastructure.
- Data Science & Platform Engineering — Build data products through ETL/ELT pipelines and real-time processing. Architect ML-as-a-Service platforms that transform data into competitive advantage.
Certifications
Industry-recognized certifications validating expertise in cloud infrastructure, container orchestration, and scalable system design—essential for deploying production-grade ML/AI platforms.
Certified Kubernetes Administrator
Cloud Native Computing Foundation
Validated expertise in Kubernetes cluster management, container orchestration, and cloud-native infrastructure.
AWS Certified Solutions Architect - Associate
Amazon Web Services
Demonstrated ability to design and deploy scalable, highly available systems on AWS for ML/AI workloads.
Education
Master of Science (MSc) in Data Science and AI
University of Liverpool, UK
- Graduated with Distinction
- Focus areas: Data Science, Machine Learning, Natural Language Processing, Applied AI
- Advanced Statistics, Data Mining, Predictive Analytics, Business Intelligence
- Reinforcement learning, Bio-Inspired Algorithms, Advanced Mathematics for AI
- Databases, Python, R, SQL, Data Visualization
Bachelor of Technology (B.Tech)
SRM Institute of Science and Technology, Chennai
- First Class with Honours
- Major: Electronics Engineering
Technical Expertise
Comprehensive data science and AI expertise focused on extracting insights, building predictive models, and delivering scalable solutions.
MLOps & Production
Cloud & Infrastructure
Infrastructure as Code
AI & Machine Learning
LLM & AI Agents
Data Engineering
Current Focus
Designing cloud-native AI platforms across OpenShift and AWS — fine-tuning open-weight models, serving inference, and delivering it all with GitOps.
Designing AI Platforms
Architecting cloud-native AI platforms across OpenShift/OKD and AWS — with Red Hat OpenShift AI (RHOAI) and Open Data Hub (ODH) — for fine-tuning open-weight models and serving scalable, low-latency inference.
GitOps & Declarative Delivery
Shipping cloud-native AI workloads through GitOps — version-controlled, automated rollouts with Argo CD, Helm, and Kustomize for reproducible environments and zero-downtime deployments.