Aryan Sharma Arynshr

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│         CS Undergrad · Applied AI & Systems             │
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I build backend systems and applied ML pipelines:- retrieval systems, LLM inference workflows, and evaluation-driven architectures. Currently focused on hybrid search and RAG systems. I read papers, implement them, and validate results.

`$ whoami`

aryan = {
    "role"      : "Applied AI/ML · Backend · Systems",
    "education" : "B.Tech CSE · JIIT Noida",
    "building"  : ["LLM inference pipelines", "hybrid retrieval systems", "RL environments"],
    "open_to"   : ["SDE", "Backend Engineering", "AI/ML Engineering", "Data Engineering"],
}

`$ cat stack.json`

Domain	Technologies
Languages	Python · C/C++ · SQL
Backend	FastAPI · Async Python · REST APIs · WebSockets · Pydantic · SQLAlchemy · PostgreSQL
AI / ML	NLP · Transformers (BERT, FlanT5) · Scikit-learn · Reinforcement Learning · spaCy
Retrieval	BM25 · FAISS · Qdrant · Dense + Sparse Search · RRF · CrossEncoder Reranking
LLM Tooling	OpenAI SDK · Groq API · LangChain · RAG Pipelines · Prompt Engineering
Infra & Dev	Docker · Git · pytest · Linux CLI · SQLite · MySQL

`$ ls -la ./projects/`

🔹 InventOps — RL Supply Chain Simulation Engine

Stack: Python · FastAPI · Groq (Llama-3.1) · OpenAI SDK · Docker · pytest · Pydantic v2

OpenEnv-style RL environment for multi-echelon supply chain optimization

Modeled stochastic demand across 25 SKUs with multi-warehouse setups and configurable difficulty levels
Reduced LLM observation token size by 87% via optimized state serialization in a Groq/Llama-3.1 pipeline
Built as a Dockerized FastAPI service with a 17-test pytest suite for validation

🔹 Scipher — Document ETL & NLP Pipeline

Stack: Python · FastAPI · Docling · BERT · FlanT5 · spaCy · SQLAlchemy · SQLite · Docker

Multi-stage pipeline for converting academic PDFs into structured data

End-to-end flow: parsing → section classification (BERT, 92% accuracy) → NER (spaCy) → summarization (FlanT5) → glossary generation
Async FastAPI service with WebSocket support, Pydantic-validated I/O, and integrated logging

🔹 HybridIR — Hybrid Retrieval System

Stack: Python · FastAPI · BM25 · Qdrant · sentence-transformers · CrossEncoder · Groq API · Tavily

Hybrid search system combining sparse and dense retrieval with reranking

BM25 + Qdrant dense retrieval fused via Reciprocal Rank Fusion (RRF) with CrossEncoder reranking
Evaluated on labeled queries using Precision@K, MRR, nDCG@5; targeting measurable improvement over BM25 baseline
Web-augmented retrieval via Tavily; side-by-side retrieval comparison UI via Textual

`$ cat /proc/current`

→ Extending HybridIR: query routing + multi-stage reranking + web-augmented retrieval
→ Evaluating LLM pipelines across latency and output quality tradeoffs
→ Studying IR metrics, vector indexing, and inference optimization

`$ echo $CONTACT`

# Open to: SDE · Backend Engineering · AI/ML Engineering · Data Engineering

echo "aryan.shr.04@gmail.com"
open "https://linkedin.com/in/arynshrma"

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