Engineer who builds
things that ship

MS Data Science from Indiana University.

addankinaveen84@gmail.com LinkedIn GitHub
Experience
Oct 2025 — Present

AI Engineer

Heartland Community Network
  • Architected AWS Bedrock multi-agent document intelligence platform with LangGraph orchestration and OCR — processed 2,000+ research papers, cutting literature review time 75%.
  • Production RAG system with OpenSearch vector store (150K+ embeddings), hybrid search, sub-second latency, 90% relevance lift.
  • Containerized GenAI services on ECS with auto-scaling; integrated BigQuery + Tableau reporting. 40% infrastructure cost reduction, 99.5% uptime.
Jan — Aug 2025

AI/ML Research Engineer

Indiana University
  • Agentic RAG with LangGraph for financial analysts — ingested 5,000+ SEC filings with hybrid retrieval across Qdrant, FAISS, ChromaDB. Evaluated with Ragas.
  • Fine-tuned Llama-3 8B/70B and VLMs with LoRA + DeepSpeed distributed training. DPO/RLHF alignment to 85% accuracy. Deployed via vLLM with GPTQ quantization.
  • End-to-end image synthesis on fine-tuned Stable Diffusion XL + CLIP with FastAPI backend.
  • Managed 50+ annotators, curated 250K+ labels at 95% accuracy for LLM/VLM training.
May — Dec 2024

Graduate GenAI Engineer

Indiana University — Eskenazi School of Art, Architecture + Design
  • Real-time Voice RAG — LangChain + STT/TTS + Pinecone hybrid search. Security safeguards, 30% irrelevant output reduction.
  • Neo4j graph-based reasoning and memory layer for conversational AI handling 3,000+ daily interactions.
  • Automated data ingestion and vector DB update pipelines. Dockerized, CI/CD with DevOps collaboration.
Sep 2021 — Jul 2023

Data Engineer

Amgen (Client)
  • XGBoost anomaly detection on SageMaker (0.95 TPR) for 20K clinical trial records with real-time FastAPI alerts.
  • Informatica ETL workflows processing 70M+ unstructured records daily.
  • CI/CD pipelines with Airflow, MLflow, Docker for reproducible model lifecycle.
Projects

Credit Document OCR + LLM Extraction

Containerized OCR pipeline — FastAPI, Celery, Redis, PostgreSQL. EasyOCR + Ollama to parse loan details from PDFs with async processing and status tracking.

FastAPI / Celery / Redis / Docker / EasyOCR

AI Terminal Coding Agent

Terminal-based coding agent using local Ollama models. ReAct-pattern architecture with memory, safe code execution, and AI integration.

Python / Ollama / ReAct pattern

Hybrid Anime Recommender

Collaborative filtering + content analysis on 100K+ entries. Flask app with MLOps (COMET-ML, DVC, Jenkins CI/CD) on GKE.

GCP / Flask / DVC / Kubernetes

JobMelan — AI Resume Optimizer

SaaS platform (Next.js 16, React 19, TypeScript, PostgreSQL) that optimizes resumes for ATS using Gemini 2.5 for parsing, keyword matching, and auto-tailoring.

Next.js / React / Prisma / Gemini API
What I Learned

Summary of what I studied across the ML stack

Over the course of my MS and self-study, I worked through 128 topics spanning linear algebra, statistics, classical ML, deep learning, NLP, computer vision, and production MLOps. I organized my notes into a structured reference that I still use for revision.

My Study Notes

12 modules · 128 topics
From math foundations through production MLOps — visual explanations, decision flows, and worked examples organized by topic.
Browse all topics →
Math Foundations 3 topics
Statistics 15 topics
SQL 2 topics
Data Engineering 2 topics
ML Core 33 topics
Unsupervised Learning 7 topics
Deep Learning 19 topics
CNNs & Vision 5 topics
NLP & LLMs 20 topics
Advanced ML 11 topics
MLOps 4 topics
Python Mastery 9 topics
Skills
AI / LLM
Fine-tuning RLHF / DPO RAG LangChain LangGraph vLLM Crew AI MCP A2A
ML / Frameworks
Python C++ PyTorch TensorFlow Keras Scikit-learn OpenCV NLTK DeepSpeed
Cloud / Infra
AWS SageMaker AWS Bedrock AWS ECS GCP Vertex AI BigQuery Docker Kubernetes MLflow Airflow
Data
SQL MongoDB Neo4j Pinecone Qdrant FAISS ChromaDB OpenSearch Snowflake
Education
Aug 2023 — May 2025

MS Data Science

Indiana University Bloomington · GPA 3.9 / 4.0
Reinforcement Learning, Statistics, Applied Algorithms, Computer Vision, Data Analytics, Deep Learning
Certifications
AWS Certified ML Engineer Amazon Web Services
Deep Learning Specialization DeepLearning.AI
Azure AI-900 / AZ-900 Microsoft