Professional Overview
Innovative MLOps Engineer with extensive experience architecting cloud-native AI solutions on a proprietary CSP platform. Led development of LLM Inferencing, Container as a Service, and Fine-Tuning as a Service using Kubernetes, KServe, vLLM, Ray Serve, and PyTorch. Expertise in container orchestration, MLOps, GPU management, and model deployment, with a proven track record as a founding AI team member driving the deployment of 50+ LLMs and scalable AI services.
Areas of Expertise
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
