Test-Time Training: When Your Model Learns During Inference
Test-time training lets models update their own weights during inference. Learn how TTT layers work, their GPU implications, and why this changes AI infrastructure.
Read Article →Hey, I'm Saurabh
I build AI infrastructure
from data pipelines to GPU kernels.
Data engineer progressing through LLMOps, GPU engineering, and RL infrastructure. I document every layer of the journey — the systems, the tradeoffs, and the things I wish someone had told me.
What I Write About
Each layer builds on the last — from reliable data systems to the frontier of RL infrastructure.
01
Data Engineering for AI
ETL pipelines, feature stores, and the scalable data infrastructure that powers everything above it.
02
LLMOps & Production AI
RAG pipelines, vector databases, LLM observability, and serving models reliably in production.
03
GPU Engineering & RL Infrastructure
CUDA kernels, distributed training, performance optimization, and building the systems behind reinforcement learning.
CAREER ROADMAP
Data Engineering → LLMOps → GPU Engineering → RL Infrastructure
I'm building toward RL infrastructure expertise — one layer at a time. Follow along as I document the progression, share what I'm learning, and build in public.
Learn More About MeLatest Posts
Notes from the transition.
LLM Observability: Tracing Your AI Applications
Learn how to add observability to LLM applications using OpenTelemetry and data engineering practices.
Read Article →Choosing a Vector Database: A Data Engineer's Guide
Compare ChromaDB, Pinecone, Weaviate, and pgvector to find the right vector database for your RAG application.
Read Article →Building a Production RAG Pipeline with Apache Airflow
Learn how to orchestrate a Retrieval-Augmented Generation pipeline using Apache Airflow and data engineering best practices.
Read Article →Prompt Version Control: Treating Prompts Like Production Code
Learn how to apply data engineering principles to manage LLM prompts with versioning, labels, and rollback capabilities.
Read Article →