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Achievement: Pull Sharkx2Achievement: YOLO

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royniel/README.md

Typing tagline

Location


  About Me

name:        Nilanjan Roy
role:        Full-Stack Engineer @ Vertige (Healthcare AI)
education:   M.S. Software Engineering + AI · Northeastern '25
focus:       Real-time distributed systems · Applied LLMs · Mobile products
mantra:      "Reliability over novelty. Latency you can feel. Code that ships."


  Tech Arsenal

Languages

Backend & Streaming

Frontend & Mobile

AI / ML

Data & Infra


  The Road So Far

🩺  Vertige         Full-Stack Engineer   Jan 2025 — Present   Philadelphia (Remote)
💼  Cynet Systems   Full-Stack Engineer   Sep 2022 — Aug 2023  Noida, India
🎟  Mastech Digital Full-Stack Engineer   Jan 2021 — Sep 2022  Noida, India


  Things I've Shipped

🎨 Canvas2Code

Image → working code, in real-time.

Multimodal LLM pipeline with SSE streaming, Postgres-checkpointed conversational state, Redis-cached vision-judge calls, per-provider budget circuit breakers, and an automated eval harness scoring visual fidelity, element presence, and code validity.

📈 LynchBot

Peter Lynch as a chatbot. RAG, no API keys.

Financial RAG chatbot with FLAN-T5 generation + Sentence-BERT semantic search, an async embedding pipeline with custom caching, and LLM eval workflows benchmarking retrieval quality against unstructured financial datasets.

  What I Optimize For

Reliability over novelty — zero-rollback releases · fault-tolerant Kafka · JUnit-first
Latency you can feel — 30% retrieval gains · 18% page load cuts · <5s cold starts
Code that ships — 5 years of production microservices, mobile apps, and AI systems users actually touched


Always open to interesting problems. Reach out 📬

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    This is trading chat bot made out of RAG model based out of Google Flan T5 and Mini LM L6

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    Turn any images to React/ Vue/ Next.js code with Gemini LLM

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    A chatbot based on Gemini API

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