Generative AI & LLM Expertise

Core Expertise in Generative AI & Large Language Models

LLM Architecture & Training

Deep expertise in transformer architectures, attention mechanisms, and distributed training strategies for models ranging from BERT to GPT-4 scale systems.

  • Custom transformer implementations
  • Multi-GPU/TPU training pipelines
  • Model optimization and quantization

Production LLM Systems

Designed and deployed enterprise-scale GenAI systems serving millions of requests daily with sub-second latency requirements.

  • Kubernetes-based inference clusters
  • Dynamic model routing and A/B testing
  • Cost optimization strategies

RAG & Vector Databases

Pioneered retrieval-augmented generation systems combining LLMs with vector search for domain-specific applications.

  • Custom embedding pipelines
  • Hybrid search architectures
  • Real-time knowledge updates

Technical Innovation Timeline

2024 - Present

Multi-Modal LLM Platform

Led development of unified platform supporting text, image, and code generation at scale.

2023

Enterprise RAG System

Architected retrieval system processing 100M+ documents with 99.9% uptime SLA.

2022

Custom LLM Training Framework

Built distributed training system reducing costs by 60% while improving model performance.

2021

NLP Pipeline Automation

Pioneered automated MLOps pipelines for continuous model improvement and deployment.

Impact Metrics

500M+
API Requests Processed
99.95%
System Uptime
60%
Cost Reduction
15+
Models Deployed
3x
Performance Improvement
50+
Engineers Mentored

Technical Stack & Tools

PyTorch TensorFlow Hugging Face LangChain Vector DBs CUDA Kubernetes Ray MLflow Apache Spark Redis Prometheus Grafana AWS SageMaker GCP Vertex AI

System Architecture Overview

Production LLM Inference Pipeline

Request Layer

Load Balancer

Rate Limiting

Auth & Security

Processing Layer

Model Router

Context Window Mgmt

Batch Optimization

Inference Layer

GPU Clusters

Model Serving

Response Streaming

Key Contributions

Research Publications

Published papers on efficient LLM inference, few-shot learning, and production deployment strategies in top-tier conferences.

Open Source Leadership

Maintained critical GenAI libraries with 10K+ GitHub stars, contributing to democratization of AI technology.

Industry Innovation

Patents pending for novel approaches to LLM caching, dynamic batching, and real-time model adaptation.