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Ruchir Bhatia / Software & AI Engineer / LA

I build software that has to be right at 300 km/h.

I'm a CS master's student at USC who ships things end-to-end: a live F1 race-strategy engine that makes pit calls from real timing data, an on-device driving co-pilot that watches the road and the driver, and customer-facing features for a product that doubled its users while I was on the team.

I care about one thing more than most: numbers I can defend. Every model on this page was tested on data it never saw, with the test written down before it was run — and where something didn't work, I say so.

📍 Los Angeles, CA—🎓 USC M.S. CS · May 2027

Experience 01

Where I've shipped code other people depend on.

Transnode AI Software Engineer Intern · letter ↗Jun – Aug 2026

Owned customer-facing features for Earnie end-to-end across React Native, iOS and web — from design through launch, including the release-blocking bugs nobody else wanted.

679 → 1,436 registered users (~111%)React Native · iOS · Web
Bharati Vidyapeeth COE ML Research AssistantJan – Jun 2024

Built a retrieval-augmented generation pipeline grounding LLM answers in structured knowledge, then profiled it until it was fast enough to feel instant.

65% lower end-to-end latencyPython · PyTorch · RAG
Redis Ltd Software Engineer Intern · letter ↗Jun – Sep 2023

Designed and tested Redis 7.2 caching workflows for high-throughput, low-latency access on AWS ElastiCache, and automated the regression suite around them.

18% less memory30% faster testing

Featured Projects 02

Real recordings of the real systems — and one you can drive yourself.

PitWall's live pit wall replaying the 2026 Azerbaijan GP lap by lap through the same engine that runs on race day: "stay out" on lap 13, "BOX, BOX — Softs" on lap 29, then "stay out to the flag". Independent project, not affiliated with Formula 1.

PitWall AI

2026 · deployed

A live Formula 1 race-strategy engine. A Bayesian tyre-wear model updates lap by lap from live timing; an exact dynamic-programming optimiser searches every 0–3 stop plan; Monte Carlo simulates safety-car risk. It makes a pit call in under three seconds.

Walk-forward on 173 driver-racesFirst-stop error 9.2 vs 10.3 laps (baseline)Stop-count accuracy 33.5% vs 27.7%

Honest note: the baseline is a naive strategy, and the margin is real but modest. F1 strategy is hard — that's why I built it.

FastAPINext.jsBayesian inferenceDynamic programmingMonte Carlo
Live app ↗Repo ↗

Screen recording of DriveMind running live on a MacBook Pro, everything on-device. Road footage: BDD100K © 2018 The Regents of the University of California, used for non-commercial, educational purposes under the BDD100K license.

DriveMind — Multimodal In-Vehicle Assistant

2026

An on-device co-pilot: YOLO11 + ByteTrack perception on the road, a driver monitor watching for drowsiness, and a 4-bit vision-language model agent you can talk to through Whisper.

Eye-state model blink F1 0.95False microsleep alerts 33/h → 010/12 unseen drowsy drivers caughtYOLO 10–18 ms/frame
Spoken question 'Is that light green?' answered on-device: Whisper 0.6 s, VLM 1.7 s, 2.3 s end to end
Ask it out loud — “Is that light green?” — and it answers on-device in about 2.3 s (Whisper 0.6 s + VLM 1.7 s).

Every drowsiness test was pre-registered and run once on drivers the system had never seen. Two earlier traffic-light tests failed — they're in the repo too.

PyTorchYOLO11MediaPipeWhisperVLM agent
Repo ↗How it was tested ↗

Sociopals

fullstack · solo

A real-time social platform designed and shipped end-to-end: authentication, access control, live messaging, and audio/video channels, on reusable APIs and a relational data model.

Next.jsTypeScriptNode.jsPrisma / MySQLSocket.io
Repo ↗

By the Numbers 03

Measured, not estimated.

0user growth at Transnode AI while I shipped features
0lower latency on a RAG pipeline
0driver-races in PitWall's walk-forward backtest
<3sfrom live timing to a pit call
10/12unseen drowsy drivers caught by DriveMind
0.95blink F1, leave-one-person-out
0memory saved on Redis ElastiCache
0publications: IEEE paper, patent, research paper

Publications 04

 

IEEE · Published
OS Scheduling & Page Replacement

Peer-reviewed analysis of page-replacement and CPU-scheduling algorithms for OS memory management.

Patent · Accepted
LLM Healthcare Chatbot

Retrieval-augmented chatbot grounded in structured medical knowledge for clinical question answering.

Research Paper
VLM4Rec: Multimodal Recommendation

Grounds item images into semantic descriptions with a vision-language model, outperforming fusion-based baselines.

Software Copyright · Registered
Page-Replacement Algorithms in Shell

Education 05

 

University of Southern California M.S. Computer Science– May 2027
CSCI 566 Deep LearningCSCI 570 AlgorithmsCSCI 642 Robot LearningDSCI 552 ML — 4.0, joint top scorer
Bharati Vidyapeeth College of Engineering B.Tech Computer Engineering– Jun 2024
GPA 3.87 / 4.00Top 5% of classAlgorithmsOperating SystemsMachine Learning

Skills 06

 

001Languages

Python, C++, TypeScript / JavaScript, SQL, Swift, Bash

002ML & AI

PyTorch, TensorFlow, LLMs, RAG, vision-language models, Whisper, YOLO, MediaPipe, XGBoost / LightGBM, honest evaluation

003Software

React, React Native, Next.js, Node.js, FastAPI, REST APIs, real-time systems, system design

004Cloud & Data

AWS (EC2, S3, ElastiCache), Redis, MySQL, Docker, Vercel, Render, Git

Let's build something.

I'm looking for full-time Software, ML and AI engineering roles starting mid-2027. The fastest way to reach me is email — I reply within a day.

✉ bhatiaruchir04@gmail.com LinkedIn ↗