AI Engineer · Melbourne, Australia
I build and ship production AI systems end to end — from LLM-powered products to clinical deep-learning tools. Master of Data Science at the University of Melbourne. Open to freelance and contract work.
Melbourne, Australia.
I'm an AI Engineer who turns research prototypes into stable, high-performing production systems. My focus is applied LLMs, RAG, and agentic AI, backed by solid cloud and full-stack engineering.
Currently pursuing a Master of Data Science at the University of Melbourne, after a B.S. in Data Science from IIT Madras. Previously Founding Engineer at evolvue.ai and a research intern at IIT Ropar building clinical AI tools.
Built the core of an AI-powered voice interview platform from scratch: LLM orchestration, real-time STT/TTS pipelines, AWS deployment (ECS/ECR/S3/RDS), CI/CD, load testing, and monitoring. Under the guidance of Krish Naik and Mayank Agarwal.
Built the initial end-to-end clinical tool that lets doctors run inference from trained DL models on 2D/3D medical images and re-annotate poor outputs to feed model fine-tuning. Now mentoring the student team continuing it.
Ran technical sessions and code reviews on MVC architecture, REST API design, and clean coding with Flask.
IIT Madras · Software Engineering
An LMS powered by GenAI that recommends personalized learning paths and answers learner questions from course content via a RAG pipeline. Local Llama 3.1 with Ollama, React + Flask + MongoDB.
IIT Madras · Deep Learning for CV
A computer-vision pipeline for waste classification and segmentation on noisy, real-world imagery — CNN training in PyTorch, an iterative relabel-and-retrain loop, and OpenCV preprocessing.
IIT Madras · Modern App Dev
A full-stack ticketing platform built solo and deployed live on AWS EC2. Flask + Vue.js, Redis caching and distributed locks, Celery background jobs, and transactional seat locks to prevent double-booking.
UniMelb · Cluster & Cloud Computing
A cloud-native system analyzing Australian opinion on solar batteries and subsidy policy. Self-provisioned Kubernetes across 6 Melbourne Research Cloud VMs, Fission serverless harvesters, Elasticsearch + Kibana, and local + hosted LLMs.
Open to freelance, contract work, and collaborations. Based in Melbourne, available remotely worldwide.