Hello, I'm

AJAY RAJ

>_

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Building AI systems that solve real-world problems

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01. About Me

I'm a Junior AI/ML Engineer focused on building intelligent software that combines AI with solid engineering. I work across the stack—from designing AI workflows and backend services to developing applications that are scalable, maintainable, and built for real-world use.

I enjoy exploring new technologies and working on systems that require more than just models, where architecture, automation, and thoughtful implementation are just as important as the intelligence behind them.

0 Major Projects
0 Internships
0 + Technologies

02. Tech Stack

Programming

Python JavaScript

AI & Machine Learning

Generative AI RAG GraphRAG LLM Integration Multi-Agent Systems LangGraph LangChain NLP MLOps Image Classification CNN Pandas TensorFlow PyTorch MLflow

Backend

FastAPI Apache Kafka Redis Celery MQTT JWT Authentication

Database

SQL pgvector PostgreSQL Pinecone Neo4j (GraphRAG)

Cloud & DevOps

AWS Docker Kubernetes GitHub Actions CI/CD Render

Other

IoT (ESP) KiCad Power BI

03. Experience

> Full-Time

Aug 2026 — Present

Junior Software Engineer

Zealogics

> Internships

May 2026 — July 2026

AI Intern

Relatore Solutions

  • Built a multi-agent AI system using LangGraph that transforms raw startup ideas into investor-ready strategy reports through specialized agents, parallel execution, and an automated consistency checker.
  • Engineered a Hybrid RAG pipeline (pgvector, BM25, RRF) backed by a metadata classification engine that auto-tags knowledge base chunks across multi dimensional categories, enabling highly targeted retrieval for individual agents.
  • Built a distributed processing pipeline on Amazon Elastic Container Service (ECS), decoupling heavy LLM inference tasks using Celery and Redis as a message broker to ensure resilient, asynchronous processing of concurrent LLM workloads without degrading API performance.
2025

Student Intern

Sasken Technologies Limited

Developed Shared Memory Whiteboard in Linux C using POSIX shared memory and semaphores, enabling multiple processes to collaboratively read and write on a shared text interface with synchronized access.

04. Projects

Demo Code
2026

Predictive Maintenance

Aircraft Engine RUL Prediction using ML

  • Developed a predictive maintenance system using Scikit-learn (Random Forest) regression to predict aircraft engine remaining useful life, achieving 11.73 MAE and 16.83 RMSE with 0.84 R².
  • Containerized with Docker and deployed on a cloud platform (Render) via FastAPI with a web interface for real-time inference. Integrated MLflow for experiment tracking, model versioning, and production staging.
Scikit-learn Pandas FastAPI Docker Random Forest MLflow
Demo Code
2025

HealthyFins

Fish Disease Detection for Pisciculture Farms

  • Built an ML – IoT system using Python and TensorFlow, training a CNN model for real-time fish disease prediction, achieving 85.33% accuracy and 0.86 F1-score across 8 disease classes.
  • Deployed the model via FastAPI on Render with a responsive web interface, integrating an event-driven telemetry pipeline using HiveMQ (MQTT) & Apache Kafka for real-time sensor ingestion, pH monitoring, alerts, and user management tailored for pisciculture farms.
TensorFlow CNN FastAPI IoT ESP8266 Apache Kafka MQTT

05. Open Source Contributions

Hugging Face Hugging Face Transformers

Identified and fixed a dict comprehension syntax bug in modeling_utils.py, resolving a ValueError; solution reviewed and validated by core project contributors.

OpenCV OpenCV

Patched CMake configuration to resolve build system deprecation warnings, improving cross-platform build reliability; contribution merged into the OpenCV 5.x branch. PR #29529.

scikit-learn Scikit-learn

Identified and fixed an inconsistency in PCA namespace validation in decomposition/base.py; contribution merged into the scikit-learn main branch. PR #34493.

06. Education & Certifications

> Education

B.Tech — Electronics & Communication Engineering

Federal Institute of Science And Technology

CGPA: 7.45

Class XII

St. Sebastian's HSS, Kadanad

Score: 97.4%

Class X

Ambika Vidyabhavan CBSE School

Score: 94.6%

> Certifications

Machine Learning using Python

NIELIT

AWS Academy Graduate

AWS Cloud Foundation

07. Get In Touch

Email

ajayraj3002@gmail.com

Phone

+91 7034928316

LinkedIn

Ajay Raj

GitHub

ajayraj30002
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