Hey, I'm Amit,

An AI/ML
Engineer
& On-Device
ML Builder

Shipping transformer models to phones, laptops, and everything in between — where the cloud isn't invited.

Amit Yadav

Field Studies

001 — 001

Small, finished software aimed at problems real companies are staffing teams to solve. One industry at a time, taken far enough to measure and then stopped.

CPG · Trade Finance2026

Shortpay

Distributors pay a brand's invoice short and attach a reason code. The brand has 90 to 180 days to dispute before the money is gone for good, and the documents proving it arrive as scans with no text layer. Shortpay reads them, reconciles every deduction against the deal sheet and delivery paperwork, and prepares the dispute.

Most tools rank disputes by dollar size. That is the wrong sort — a $400 claim closing on Friday is worth more than a $4,000 claim with 90 days left, because only one of them is about to become zero.

On-Device Inference

CoreML, quantization, Swift tokenization.

CoreML
Swift
Hugging Face
LLM Fine-Tuning

Unsloth, domain datasets, MLOps loop.

PyTorch
Unsloth
Hugging Face
Full-Stack ML

Data pipelines → API → AWS deploy.

AWS
Docker
FastAPI
Open Source

sktime, Kiwix/openZIM, upstream contributions.

GitHub
sktime
Kiwix

Building ML that runs where people actually are.

I work on the seam between Hugging Face and constrained hardware — closing the gap between a 7B model on a research cluster and a quantized transformer running inside an iPhone. That throughline connects everything I build: Cortex, my on-device LLM research at BU, and the Gutenberg semantic-search work I'm proposing for GSoC 2026. When the cloud isn't available — or isn't welcome — the model still has to be there.

Selected Work

001 — 003
Cortex
SwiftCoreMLDistilBERTSwiftData
iOS · On-Device

Cortex

A privacy-first iOS bookmark manager where a DistilBERT model auto-tags links fully on-device — no accounts, no round-trips, no telemetry. The trickiest part was making the model optional: if the weights aren't bundled, the app falls back to Apple's NaturalLanguage framework so tagging still works on a slim build. SwiftData handled persistence almost invisibly, which let me spend the time on the part I actually cared about — tuning the tag vocabulary until the suggestions felt like mine.

Built with
iOS
Swift
CoreML
Hugging Face
Xcode
Smart Energy Optimizer
SwiftUIIBM watsonxGranite-3WebSockets
IBM TechXchange Hackathon · 2025

Smart Energy Optimizer

Built in a weekend for the IBM TechXchange hackathon: a SwiftUI dashboard that streams live telemetry over WebSockets from a Node/Express backend wrapping IBM watsonx's Granite-3-8b for 24-hour load forecasting and peak-shaving tips. The backend fakes a house full of HVAC and lighting through a simulator, which turned out to be the right call — we could demo the whole loop without anyone rewiring an apartment. I pushed the socket layer to a 30-second heartbeat so the SwiftUI side could stay purely reactive via @Observable instead of babysitting polling timers.

Built with
Swift
iOS
Node.js
JavaScript
Docker
Modern Data Warehouse
PostgreSQLPL/pgSQLMedallion ETLTableau
Data Engineering

Modern Data Warehouse

An end-to-end ETL pipeline in pure PostgreSQL and PL/pgSQL — no Airflow, no dbt, no managed warehouse. Raw sales data moves through a Bronze → Silver → Gold medallion architecture and lands in a star schema ready for Tableau. It's the least flashy project in my portfolio and the one that taught me the most about why the boring parts of data engineering — keys, grain, idempotent loads — are the parts that actually matter.

Built with
PostgreSQL

Entrepreneurship

All Stories

Writing

All Posts