# Thillai Chithambaram > ML Engineer | LLM Systems, Scalable Inference & GenAI Infrastructure | Computer Vision | vLLM Contributor | MS @ Stony Brook Location: Stony Brook, New York, United States Profile: https://flows.cv/thillai ML Engineer building high-performance LLM systems and scalable generative AI infrastructure, focused on turning cutting-edge research into production-ready systems that operate at scale. My work sits at the intersection of model intelligence and systems engineering. I design agentic LLM pipelines, optimize inference at the kernel and serving level, and build end-to-end AI systems that prioritize latency, throughput, and reliability. From multi-agent reasoning systems to multimodal perception pipelines, I focus on pushing both capability and efficiency. ▪ What I do best: Building and optimizing LLM systems (RAG, agents, tool use), accelerating inference with KV cache optimization, quantization, and TensorRT, and deploying scalable architectures using vLLM, PyTorch, and distributed training (FSDP, DDP). ▪ Real-world impact: Delivered production-grade LLM systems that improved retrieval accuracy by 38% and reduced latency by 45%, built aerospace vision systems with 98.8% precision, and developed medical AI models ranking among top global benchmarks. ▪ Open source & systems mindset: Active contributor to LLM inference ecosystems including vLLM and llm-d, with contributions spanning scalable serving, performance optimization, and knowledge editing (EasyEdit) for improving factual control and model reliability. ▪ Core focus areas: LLM systems • Agentic AI • Scalable inference • Multimodal models • Distributed ML systems ## Work Experience ### Open Source Contributor @ vLLM Jan 2026 – Present Enhanced performance metrics for quantized LLMs by expanding support from 3 to 22+ quantization methods (including GPTQ, AWQ, BitsAndBytes, and FP8 variants). Refactored quantization parsing logic and introduced unified weight mappings to improve accuracy of FLOPs and memory estimation, with added test coverage for robustness. ### Research Assistant @ Stony Brook University Jan 2025 – Present | Stony Brook, New York, United States Focusing on LLM knowledge editing, investigating methods to update and refine model knowledge without full retraining. Designing evaluation pipelines, running large-scale experiments, and analyzing robustness, locality, and generalization of edits. ### Applied AI Engineer Intern @ Zideas LLC Jan 2025 – Jan 2025 | New York City Metropolitan Area Developed an autonomous LLM-powered web crawler to extract and validate KYC documents from multiple regulatory websites. Implemented an agentic RAG architecture with scalable storage and optimized retrieval for efficient access to compliance information. ### Computer Vision Researcher @ ISRO - Indian Space Research Organization Jan 2024 – Jan 2024 | Bengaluru, Karnataka, India Conducted research on X-ray radiography images from welding inspections, developing deep learning models to detect fusion flaws with high precision. Worked alongside engineers to streamline inspection workflows using MLOps pipelines and enhance the reliability of quality checks. ### Research Intern (Medical Imaging) @ Indian Institute of Technology, Tirupati Jan 2023 – Jan 2023 Researched advanced transformer architectures for medical imaging, implementing UniFormer to analyze multi-phase MRI scans for liver lesion diagnosis. Applied specialized loss functions to address class imbalance and ranked among the top 15 teams globally in the MICCAI Liver Lesion Challenge. ### Research and Development Head @ ACM-VIT CHAPTER Jan 2022 – Jan 2023 ### Core Research Member @ ACM-VIT CHAPTER Jan 2021 – Jan 2022 ### Machine Learning Engineer @ Bill OK Jan 2022 – Jan 2023 | Thane, Maharashtra, India Built an OCR model integrated with a language model to process invoices and extract essential fields with high accuracy, minimizing manual effort in financial operations. Implemented an automation pipeline linking the system with WhatsApp and email, enabling seamless large-scale invoice processing. ### Delegate @ Harvard Project for Asian and International Relations (HPAIR) Jan 2022 – Jan 2022 ## Education ### Master of Science - MS in Data Science Stony Brook University ### Bachelor of Technology - BTech in Computer Science and Engineering Vellore Institute of Technology ## Contact & Social - LinkedIn: https://linkedin.com/in/thillaic - Portfolio: https://www.thillaic.com/ - GitHub: https://github.com/thillai-c - Portfolio: https://thillaic.com --- Source: https://flows.cv/thillai JSON Resume: https://flows.cv/thillai/resume.json Last updated: 2026-04-18