About01Experience02Projects03Publications04Contact05
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Hello, I'm Ajaydeep

Final Year · B.Tech IT · Noida

Building production systems at the intersection of backend engineering and applied AI : from scalable APIs to end-to-end ML pipelines.

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About

Crafting useful systems with thoughtful AI and backend engineering.

I design backend-first products and applied AI workflows that solve real problems. My work spans ML evaluation, production APIs, and scalable data systems.

Published research in a CRC Press volume
Built clinical ML pipelines with reproducibility in mind
Delivered real-time data and aggregator systems

My Tech Stack

TypeScript icon

TypeScript

React icon

React

Next.js icon

Next.js

FastAPI icon

FastAPI

Node.js icon

Node.js

REST APIs icon

REST APIs

PostgreSQL icon

PostgreSQL

MongoDB icon

MongoDB

Redis icon

Redis

Docker icon

Docker

AWS icon

AWS

GitHub icon

GitHub

Vercel icon

Vercel

02 — Experience

Where I've worked.

Dec 2025 — Feb 2026

Internship · Remote

AI Intern

@ Infosys Springboard
  • Completed a virtual internship on Autonomous Cognitive Systems focused on long-term task execution using AI and deep research techniques.
  • Learned about intelligent agents, task planning, and system design for autonomous decision-making.
  • Explored real-world applications of AI and improved problem-solving and research skills.
AIAgentsTask PlanningResearchSystem Design

June 2025 — July 2025

Internship · Noida

Machine Learning Intern

@ CoE-AIE
  • Built an end-to-end multimodal ML pipeline using audio and textual data from 140+ real-world clinical interview sessions.
  • Automated speech isolation and feature extraction workflows, reducing preprocessing time by ~40%.
  • Engineered and evaluated paralinguistic and textual features using COVAREP, training models with improved F1-score.
  • Designed reproducible training and evaluation workflows with feature-importance–driven error analysis.
PythonCOVAREPFeature EngineeringNLPScikit-learn

Nov 2024 — Apr 2025

Freelance

LLM Evaluation Analyst

@ Outlier
  • Evaluated LLM outputs for hallucination, factual accuracy, reasoning and policy adherence across diverse task types.
  • Designed adversarial and edge-case prompts to stress-test LLM behavior and identify systematic failure modes.
  • Applied prompt engineering techniques (few-shot, CoT) to improve output consistency across task domains.
  • Conducted qualitative and quantitative analysis of response quality to improve LLM evaluation workflows.
LLM EvaluationPrompt EngineeringAdversarial TestingCoTRLHF

03 — Projects

Selected work.

Click to expand ↓

01

Evaly

Learning Systems · Full Stack+

Overview

Adaptive assessment platform leveraging IRT, Knowledge Space Theory, and LLM-driven personalized learning workflows. Built a full-stack adaptive learning platform with 8 modes using Next.js, PostgreSQL, IRT, and LLM-based personalization.

Highlights

  • 3PL-IRT engine for subtopic-wise ability estimation with convergence in 5–15 questions
  • Gemini integration for difficulty-controlled question generation and learner profiling
  • 101-node Knowledge Space graph with concept clustering over 3,900+ questions
  • Sub-500ms APIs and live deployment at evaly.in

Stack

Next.jsTypeScriptPostgreSQLReact FlowTailwind CSSGemini APIJWTVercel

Period

Jan 2026 — May 2026

Evaly preview 1
02

Orderly

Backend Systems · Data Engineering+

Overview

A real-time e-commerce aggregator unifying product search across Amazon, Flipkart, Blinkit, and Zepto. Built a retrieval and matching pipeline using TF-IDF, attribute filtering, and fuzzy similarity achieving 85% match accuracy. The backend handles concurrent requests with sub-second latency via Redis caching and MongoDB indexing.

Highlights

  • TF-IDF + fuzzy similarity pipeline with 85% match accuracy
  • Sub-second latency under concurrent load via Redis caching
  • FastAPI backend deployed on AWS with Docker containers
  • Presented at IC3-2025 International Conference

Stack

PythonFastAPIPlaywrightMongoDBRedisDockerAWSVercel

Period

Jan 2025 — May 2025

03

SageML

ML Systems · Research+

Overview

A modular, end-to-end ML orchestration framework built for automated training, evaluation, and GenAI-oriented workflows. Designed with RAG- and LLM-oriented abstractions supporting both structured and unstructured data with configurable NLP pipelines. Published as a book chapter in CRC Press's Generative AI: Technology and Applications.

Highlights

  • Modular pipeline abstractions for structured + unstructured data
  • RAG and LLM-oriented design with grounding and evaluation focus
  • Configurable NLP pipelines with automated preprocessing
  • Published in CRC Press book chapter (Chapter 8)

Stack

PythonPyQt6PandasNumPyScikit-learnTesseract OCR

Period

Aug 2024 — Nov 2024

04 — Publications & Achievements

Research & recognition.

Published Work

Book Chapter2024

SageML: An Automated Machine Learning Pipeline Framework

Generative Artificial Intelligence: Technology and Applications, Chapter 8

CRC Press

Conference Paper2025

ORDERLY: An Intelligent Hybrid Platform for Online Shopping System

17th International Conference on Contemporary Computing (IC3-2025)

Noida, India

Certifications & Achievements

Data Science Professional 2025

Oracle Certified Professional

Principles of Generative AI

Infosys Springboard

API Fundamentals Student Expert

Postman Academy

State Rank 8 — National Science Olympiad

Achievement

05 — Contact

Let's build
something.

Open to internships, full-time roles, and interesting collaborations. Whether it's a backend system, an AI pipeline, or a research project — reach out.