AI/ML Engineer • RAG & LLM Systems
Building production AI systems that actually ship.
I design and build reliable AI infrastructure—RAG pipelines, LLM orchestration, and real-time inference systems.
Selected Work
Projects
Brckt
Production RAG system for real-time tennis analytics.
CodePilot
Multi-agent AI system for autonomous code generation.
ML-Monitor
Production MLOps platform for real-time fraud detection.
VerbaQuery
Industrial RAG with hybrid retrieval (BM25 + dense embeddings) and cross-encoder re-ranking for enterprise document search.
About
Background
MS in Computer Science from Indiana University with a 3.9 GPA. Focused on making machine learning work in production.
My work spans RAG systems, LLM pipelines, and MLOps infrastructure. I care deeply about building AI that's reliable, fast, and actually useful.
Experience
AI/ML Engineer
2024 — PresentBuilding real-time sports analytics with LLM streaming inference on a 4-person ML team. Reduced latency from 3s to 400ms using chunked streaming and model quantization. Led optimization sprint, collaborated with backend engineers on API design, mentored junior engineer on streaming patterns.
AI Engineer
2024Architected production RAG systems for enterprise document search. Improved retrieval relevance from 67% (BM25 baseline) to 94% using hybrid search and cross-encoder re-ranking. Coordinated with Product, DevOps, and enterprise clients. Presented technical architecture to C-suite stakeholders.
Tech Stack
Contact
Let's build something
Currently open to AI/ML engineering opportunities. If you're building something interesting, I'd love to hear about it.
ayushkumarmalik10@gmail.comWhat I'm Looking For
High-impact AI roles
Teams shipping real ML products to production—not just prototypes.
Hard problems
RAG at scale, LLM orchestration, real-time inference systems.
Strong engineering culture
Code reviews, testing, and ownership over ML systems end-to-end.