Professional Overview
MLOps & AI Platform Engineer with hands-on experience designing Kubernetes-native control planes, KServe multi-model serving platforms, and Kubeflow continuous learning pipelines. Proven track record of improving GPU utilization by 40% and cutting operational costs by ~80% on real-time AI systems.
Areas of Expertise
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.
AI Product & Strategy
Translate AI capabilities into product roadmaps, define success metrics, and drive adoption across engineering and business teams.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
