I build intelligent systems — from foundation models and LLM pipelines to production-ready AI tools.
Designed zero-shot and linear-probe experiments with the FLAIR vision-language model for diabetic retinopathy and glaucoma detection, achieving 0.92 AUROC with only 5-20% labels.
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A config-driven CLI and Streamlit dashboard that ingests raw documents and generates multi-task LLM datasets (summarisation, Q&A, key-point extraction) with built-in QA evaluation scripts.
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Fine-tuned a LLaMA-style model on natural-language / SQL pairs using LoRA and parameter-efficient techniques, benchmarking query correctness and execution success against the base model.
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I'm an AI / Machine Learning Engineer with a Master of Artificial Intelligence from Monash University. My work spans foundation models, large language models, and computer vision — from building retinal disease classifiers to fine-tuning LLMs for text-to-SQL generation.
Currently a Business Fellow at Perplexity AI, I prototype LLM agent workflows and explore AI product strategy. I'm passionate about taking projects from experimentation through to production-ready tools and demos.
Download ResumePerplexity AI
Selected into a competitive fellowship focused on AI product strategy and LLM-powered workflows. Prototyping no-code and low-code LLM agent workflows to automate internal analysis tasks.
Monash University
Designed experiments comparing zero-shot vs linear-probe adaptation of the FLAIR vision-language model for retinal disease detection. Built reproducible Python/PyTorch pipelines for the full research workflow.
1337 Ventures
Researched ~400 Malaysian startups, categorising companies by sector, stage and traction to map the early-stage ecosystem and support deal flow.
DeepLearning.AI · Coursera
DeepLearning.AI · Coursera
DeepLearning.AI · Coursera
Google · Coursera
Got a project in mind, a question, or just want to say hi? I'd love to hear from you.
pugalenthi0928@gmail.comOr send me a message directly