About Me
I am an AI & Machine Learning Engineer based in San Francisco, California, with a passion for building intelligent systems that solve real-world problems. My focus is on Generative AI, LLM application development, and multi-agent systems — designing architectures that go beyond simple text generation to deliver reliable, grounded, and production-ready AI solutions.
I specialise in building end-to-end AI pipelines using LangChain, LangGraph, and Retrieval-Augmented Generation (RAG), integrating large language models with real data sources, memory systems, and evaluation frameworks. I believe the most impactful AI systems are not the ones powered by the biggest models, but the ones with the most thoughtful architecture.
Education
PU
Applied Generative AI Specialization
Purdue University
Sep 2025 – May 2026 · Credential ID: 177251303
Completed an advanced course on Applied Generative AI, focusing on end-to-end system design using LLMs. Built workflows leveraging LangChain, agentic frameworks, and RAG for contextual reasoning. Explored Transformers, VAEs, GANs, and diffusion models. Worked on LLM fine-tuning, prompt optimisation, evaluation metrics, benchmarking, and GenAI governance.
Prompt Engineering RAG LLM Fine-Tuning LangChain Agentic Frameworks Transformers VAEs · GANs · Diffusion Models GenAI Governance LLM Benchmarking
U
of T
of T
Intelligent Agents, Artificial Intelligence
University of Toronto School of Continuing Studies
Jan 2025 – Apr 2025
Innovated and created models, tools, and algorithms to tackle real-world challenges in AI. Built LLM-powered agentic applications without the constraints of off-the-shelf solutions, using LangGraph, LangChain, CrewAI, and RAG. Project: github.com/nselvar/AIStudentHelper
AI Agents LangGraph LangChain CrewAI RAG LLM Apps Generative AI
UC
Berkeley
Berkeley
Certificate Program in Data Science & Machine Learning
UC Berkeley Extension
Oct 2019 – Mar 2022
Courses: Machine Learning with TensorFlow · Practical Machine Learning (with R) · Introduction to Machine Learning Using Python · Data Science Principles and Practice Using Python · Introduction to Data Science
Machine Learning TensorFlow Python R Data Science Statistical Analysis
UC
San Diego
San Diego
Certificate, Cloud Services for Machine Learning
UC San Diego Extended Studies
Jun 2020 – Aug 2020
Cloud ML AWS Cloud Computing
AI & ML Skills
Generative AI & LLMs
LangChain LangGraph CrewAI RAG Prompt Engineering LLM Fine-Tuning AI Agents OpenAI GPT-4 / GPT-3.5 LLM Benchmarking GenAI Governance
Generative Model Architectures
Transformers Diffusion Models GANs VAEs Stable Diffusion
ML / DL
Scikit Learn TensorFlow Keras Deep Learning Neural Networks NLP
Data & Analytics
Pandas NumPy SciPy Statistical Analysis Feature Engineering
Visualization
Matplotlib Plotly Nivo Charts
Programming
Python R
