Professional Overview
Senior AI/ML Engineer with nearly 10 years of experience building production ML systems, LLM applications, and scalable AI infrastructure. Specialized in RAG, agentic workflows, recommendation systems, fraud detection, ranking models, and predictive analytics using PyTorch, XGBoost, LightGBM, LangChain, LangGraph, and cloud-native technologies.
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built production LLM apps with Next.js, Node.js, and OpenAI APIs
- Built RAG systems using vector databases and enterprise data
- Designed agentic AI workflows using tool/function calling
- Built LLM observability for latency, cost, and quality tracking
- Created LLM evaluation pipelines to reduce hallucinations
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built ML ranking and recommendation systems to improve search relevance
- Developed LLM-powered conversational assistant for property discovery
- Designed ETL pipelines and feature stores for ML personalization systems
- Built NLP pipelines to extract structured data from unstructured documents
- Created ML lead scoring and segmentation systems to improve targeting
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built recommendation and ranking systems for product discovery
- Built real-time fraud detection using streaming ML models
- Developed ML training and inference pipelines
- Worked on distributed low-latency event processing systems
- Productionized ML models for risk and decision systems
Education
Field of Study: Computer Science
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.
