Available for AI & ML Engineering Roles

Hi, I'm Md Ahmod Akram

I build |

AI Engineering student at Aligarh Muslim University specializing in Generative AI, Agentic Workflows (LangGraph / LangChain), RAG Architectures, and production machine learning systems.

from langgraph.graph import StateGraph, END
from langchain_openai import ChatOpenAI

# Define Agent State & Workflow
workflow = StateGraph(AgentState)
workflow.add_node("researcher", run_web_search)
workflow.add_node("rag_retriever", query_vector_store)
workflow.add_node("synthesizer", generate_response)

workflow.set_entry_point("rag_retriever")
workflow.add_edge("rag_retriever", "synthesizer")
app = workflow.compile()
from langchain_community.vectorstores import Chroma
from langchain_community.embeddings import HuggingFaceEmbeddings

embeddings = HuggingFaceEmbeddings(
    model_name="BAAI/bge-small-en-v1.5"
)
vector_db = Chroma(
    collection_name="ai_knowledge",
    embedding_function=embeddings
)
results = vector_db.similarity_search(query, k=5)

[INIT] Agent StateGraph compiled successfully.

[VECTOR DB] Loaded 1,420 embeddings into ChromaDB.

[PROMPT] User: "Deploy end-to-end Property Predictor on AWS"

[AGENT ACTION] Executing tool: Streamlit + SVR pipeline...

[STATUS 200] Model active. Accuracy: 95.4% | AWS Endpoint Ready.

0

+

AI & ML Projects

0

+

LeetCode Problems

0

%

Model Accuracy Benchmark

0

+

GitHub Contributions

Discover My Journey

About Me

Md Ahmod Akram Choudhury

Postgraduate Student (MCA) at Aligarh Muslim University

Karimganj, Assam, India

I am an ambitious AI Engineer and Generative AI Developer with a passion for designing autonomous multi-agent systems, retrieval-augmented generation (RAG) pipelines, and production-ready machine learning solutions.

Currently pursuing my Master of Computer Application (MCA) at Aligarh Muslim University, I bridge the gap between cutting-edge AI research and scalable software engineering.

Agentic Architectures

Designing stateful multi-agent graphs with LangGraph, LangChain & OpenAI API.

Full-Cycle MLOps

From EDA, feature engineering to model deployment on AWS with Streamlit & Docker.

Generative AI & LLMs

Developing RAG applications, vector search indexes with FAISS & ChromaDB, prompt engineering, and LLM fine-tuning.

Machine Learning & Data Science

Hands-on expertise with PyTorch, TensorFlow, Scikit-learn, exploratory data analysis, and predictive modeling.

Full Stack AI Integration

Integrating AI model microservices using FastAPI, Flask, React.js, Tailwind CSS, and SQL/NoSQL databases.

Portfolio Showcase

Featured Projects

Generative AI

Autonomous Multi-Agent RAG Assistant

Self-correcting research agent built using LangGraph & LangChain with vector retrieval, query re-writing, and dynamic tool calling.

LangGraph LangChain ChromaDB OpenAI
Deep Learning

Deep Churn & Sentiment Engine

Neural network architecture for 98% precision churn forecasting & NLP medical consultation sentiment classification.

PyTorch TensorFlow HuggingFace Flask
Full Stack AI

Local Privacy LLM Workspace

Privacy-first desktop workspace tool running local Ollama LLMs for code auditing, summary generation, and offline PDF analysis.

React FastAPI Ollama Tailwind
Technical Stack

Skills & Technologies

AI & Generative AI

Agents, LLMs, Vector Search & Neural Networks

LangGraph
LangChain
LangSmith
RAG Pipelines
ChromaDB / FAISS
PyTorch
TensorFlow
Hugging Face

Languages & Core CS

Programming Languages & Data Structures

Python
C++
Java
JavaScript
SQL
HTML5 / CSS3

ML Frameworks & DBs

Data Processing & Web Backend

Scikit-learn
Pandas / NumPy
FastAPI
Flask
React.js
MySQL / PostgreSQL
MongoDB

Cloud, MLOps & Tools

Deployment, Containers & Productivity

AWS (EC2, S3)
Docker
Git / GitHub
Streamlit
Linux / Bash
Ollama

Frontiers & Currently Exploring

Agentic Workflows

Designing multi-agent autonomous decision loops using LangGraph with state persistence.

Advanced RAG

Query routing, contextual compression, self-querying, and graph retrieval.

LangSmith Tracing

LLM evaluation, cost optimization, latency tracking, and execution debugging.

High-Throughput Inference

vLLM, vector search concurrency, and low-latency cloud model endpoints.

Developer Metrics

Coding Activity

GitHub Profile Analytics

Open source contributions & repositories (@mdakram2001)

GitHub Stats GitHub Streak

LeetCode Metrics

Data structures & algorithmic problem solving (@akram2001)

LeetCode Heatmap
Academic Background

Education & Credentials

Postgraduate Degree

Master of Computer Application (MCA)

Aligarh Muslim University, Aligarh

CGPA 8.5 / 10.0

Specialized in Artificial Intelligence, Machine Learning, Data Structures & Algorithms, Advanced Database Systems, and Cloud Computing.

Machine Learning Algorithms DBMS Software Engineering
Undergraduate Degree

Bachelor of Science (B.Sc)

Aligarh Muslim University, Aligarh

CGPA 7.3 / 10.0

Focused on Computer Science fundamentals, Higher Mathematics, Physics, and Statistical Methods for Data Analysis.

Computer Science Mathematics Statistics
Get In Touch

Let's Connect

Let's build something extraordinary together.

Whether you have an exciting AI role, a generative AI project, or want to discuss machine learning systems, feel free to drop me a message!

Location

Karimganj, Assam, India

Official Website akramchy.app
Quick Subject: