I'm Thillai,
an ML Engineer
building scalable AI
systems.
Learn More ↓
About Me
About Me
I'm an ML Engineer specializing in LLM systems, scalable inference, and production-scale GenAI infrastructure. Currently pursuing my Master's in Data Science at Stony Brook University.
My work centers on optimizing LLM inference pipelines - from FlashAttention and speculative decoding to KV cache optimization and CUDA kernel profiling. I build systems that serve models faster and more efficiently at scale.
I'm an active open source contributor to vLLM, llm-d, and EasyEdit, working on the infrastructure that powers LLM serving for thousands of developers. Previously, I've shipped production AI systems at Zideas LLC and conducted research at ISRO and IIT.
What I bring to the table:
Experience
Work Experience
Research Assistant
Stony Brook University - New York, USA
- Researching LLM knowledge editing methods and unsafe compliance behavior - investigating how models produce unsafe content in response to unsafe requests through measurable evidence from the pretraining corpus.
- Developing evaluation frameworks to trace model safety failures back to pretraining data, enabling targeted interventions for improving LLM alignment and safety.
Applied AI Engineer Intern
Zideas LLC - New York, USA
- Built a production-grade LLM document intelligence system to autonomously crawl, parse, and validate KYC artifacts across multiple regulatory sources.
- Designed an agentic hybrid RAG + vector indexing architecture with optimized LLM inference via prompt compression and caching.
Computer Vision Researcher
ISRO - Liquid Propulsion Systems Centre, Bengaluru
- Developed a visual defect detection pipeline for X-ray radiography analysis of welded aerospace components using deep learning.
- Designed a SegFormer-based segmentation model integrated with Kubeflow pipelines for automated quality inspection workflows.
Research Intern
Indian Institute of Technology, Tirupati
- Implemented a UniFormer transformer model for liver lesion diagnosis from multi-phase MRI scans.
- Ranked among the top 15 teams globally in the MICCAI Liver Lesion Diagnosis Challenge.
Machine Learning Engineer
BillOK
- Built an OCR model integrated with a language model to process invoices and extract essential fields for financial operations.
- Implemented an automation pipeline linking the system with WhatsApp and email for large-scale invoice processing.
Open Source
Contributions
vLLM
vllm-project
A high-throughput and memory-efficient inference and serving engine for large language models. Contributed to core infrastructure, improving serving performance and developer experience.
View on GitHub ↗
llm-d
llm-d
Distributed LLM serving infrastructure designed for Kubernetes-native deployments. Contributed to the disaggregated serving architecture and deployment tooling for scalable LLM inference.
View on GitHub ↗
EasyEdit (ACL 2024)
zjunlp
An easy-to-use knowledge editing framework for large language models. Contributed to improving model editing capabilities and extending the framework's support for new editing methods.
View on GitHub ↗Education
Academic Background
M.S. in Data Science
Stony Brook University
Expected Graduation: May 2026
B.Tech. in Computer Science and Engineering
Vellore Institute of Technology
Graduated: May 2024
Competencies
Technical Skills
Languages
ML & Inference
Cloud, DevOps & Agents
Highlights
Featured Highlights
Harvard Project for Asian and International Relations
Delegate for HPAIR Asia Conference 2022
Selected as a delegate for the prestigious HPAIR Asia Conference 2022 in New Delhi, presenting on AI solutions for global crises and climate change.
Research Paper - IEEE
Deep Learning-driven Detection of Nuclear Fusion Ignition
Investigated three deep learning architectures - Transformers, LSTM, and ResNet50 - for nuclear fusion event detection. Transformers achieved the highest accuracy.
Read Paper ↗
Research Paper - IEEE
Martian Terrain Classification through Federated Learning
Developed a novel federated learning approach for multi-class Martian terrain classification using DenseNet-121 architecture while preserving data privacy.
Read Paper ↗
Association for Computing Machinery (ACM)
Research and Development Head of ACM-VIT Chapter
Served as R&D Head in 2023, fostering a research-oriented culture through Data Science workshops and mentoring aspiring researchers.
Review Article - MDPI
Exploring Huntington's Disease Diagnosis via AI Models
Comprehensive review of AI-powered algorithms for Huntington's Disease diagnosis, analyzing clinical, genetic, and neuroimaging data.
Read Paper ↗Portfolio
Latest Projects
Multi-Agent AI
Agentic Research Assistant
Multi-agent AI system that automates academic research, literature review, and research paper generation using advanced LLM agents.
View Project ↗
Vision-Language Models
Vision Language Driving Perception
VLM fine-tuning pipeline for autonomous driving with distributed training, TensorRT optimization, and custom evaluation metrics.
View Project ↗
Mental Health AI
CBT-Copilot
Fine-tuned Llama-3.2-3B-Instruct for compassionate CBT-style therapeutic conversations while maintaining professional boundaries.
View Project ↗
Generative AI
Flash AI Search Engine
AI-powered search engine using Gemini 2.0 Flash with live web search results for fast, precise, source-backed answers.
View Project ↗
Generative AI
Dynamic Benchmarking Framework
Dynamic benchmarking framework evaluating LLM accuracy using real-time, location-specific data from WeatherAPI.
View Project ↗
Astroinformatics
Continual LIGO Glitch Detection
Continual learning architecture for LIGO glitch detection using Vision Transformer, achieving 93.4% accuracy in glitch classification.
View Project ↗
Generative AI
MediQuill LLM
Fine-tuned Llama-2 7B on curated medical Q&A data for accurate diagnoses, treatment recommendations, and drug information.
View Project ↗
Astroinformatics
Super Resolution Astronomical Denoiser
SRGAN for galaxy image denoising, improving PSNR by 32.7% and SSIM by 19.8% using transfer learning techniques.
View Project ↗
Fitness Analytics
AI-powered Virtual Fitness Trainer
Real-time exercise tracking using Mediapipe for body landmark detection, angle calculation, and form correction feedback.
View Project ↗