Md. Hasan Imon | AI & ML Engineer

Hi!
I'm Hasan Imon

Designing full-stack AI solutions that learn, reason, and act autonomously.

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I am
Full-Stack AI/ML Engineer.

Empowering the future with AI that thinks, learns, and collaborates.

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About Me

Who Am I?

I'm Md Hasan Imon — an experienced AI/ML Engineer from Bangladesh specialising in Machine Learning, NLP, Deep Learning, Generative AI, LLM Fine-Tuning (LoRA/QLoRA), Agentic RAG Pipelines, and Vector Databases. Over multiple production-grade projects I've designed and deployed end-to-end, multi-agent, tool-augmented AI systems that deliver measurable business outcomes through reasoning, automation, and intelligence at scale.

With strong proficiency in FastAPI, Flask, Docker, and CI/CD with Backend-as-a-Service (BaaS), I ensure every system is enterprise-ready, modular, and deployable across real-world environments. My work bridges deep technical design with business impact — enabling organisations to harness AI for smarter decisions, scalable automation, and real competitive advantage.

AI Engineer

ML Engineer

NLP Engineer

Backend & MLOps

30+ projects delivered successfully — let's build something great!

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What I Do

My Expertise

Full-Stack AI/ML Engineering

Designing end-to-end AI/ML pipelines from data to deployable applications.

Generative AI & Agentic Systems

Crafting modular agentic workflows with memory-integrated generative AI architectures.

Model Fine-Tuning & Optimisation

Fine-tuning LLMs using LoRA, QLoRA, PEFT, and quantisation techniques.

Autonomous & Tool-Augmented Reasoning

Enabling intelligent decision-making via tools, memory, and multi-agent planning.

Supervised / Unsupervised DL

Building intelligent systems using structured, labeled, and unlabeled datasets efficiently.

Model Deployment & MLOps

Deploying scalable ML models using Streamlit, FastAPI, Docker, and CI/CD pipelines.

Cups of Coffee

Projects

Clients

Partners

My Specialty

My Skills

I specialise in building full-stack, real-world AI/ML systems using cutting-edge technologies such as Agentic AI, LangGraph, LLM Orchestration, and Multi-Agent Architectures. My work focuses on intelligent planning, reasoning, and tool-augmented AI assistants.

Programming & Data

Python Bash / Shell Pandas NumPy Matplotlib Seaborn Data Analytics PySpark

Machine & Deep Learning

Supervised Learning Unsupervised Learning Classification & Regression Computer Vision Time Series PyTorch TensorFlow Scikit-learn XGBoost & LightGBM

NLP & LLMs

Transformers (Hugging Face) spaCy & NLTK Embeddings GPT & Claude LLaMA & Mistral vLLM & Ollama Fine-Tuning (SFT, PEFT, LoRA, QLoRA)

AI Agents

Multi-Agent Systems LangChain & LangGraph CrewAI & Autogen AgentOps & LangSmith Agentic RAG Tool-Augmented Agents Prompt Engineering

Databases & Vector DBs

MySQL & PostgreSQL MongoDB Redis (Caching) Pinecone & Qdrant FAISS & ChromaDB

Cloud, MLOps & Backend

FastAPI & Flask REST APIs & OOP AWS & GCP Docker & Kubernetes Linux & Nginx CI/CD & GitHub Actions MLflow & W&B PyTest

Background

Education

Bachelor of Science in Computer Science & Engineering

Pursuing BSc in Computer Science and Engineering from City University, Dhaka, Bangladesh. Specialised in Software Engineering principles with a focus on real-world applications.

Actively building industry-grade AI systems, participating in research, and contributing to open-source AI/ML projects during academic years (2022 – 2025).

Higher Secondary Certificate (HSC)

During this phase I focused entirely on academic excellence in science subjects including Physics, Chemistry, Mathematics, and Biology. This period laid the foundational knowledge and discipline that later shaped my journey into AI/ML engineering.

Secondary School Certificate (SSC)

Successfully completed the SSC under the Dinajpur Board, laying the academic foundation in core subjects — the starting point of my educational journey.

Career

Work Experience

Junior ML Engineer @ Codixel January 2026 – Present

Working as a Backend AI Engineer focused on building production-grade multi-agent AI systems. Developed and maintained agentic workflows using LangGraph and AgentOps orchestration. Implemented tool-augmented pipelines (PDFs, Web, APIs, Databases) and integrated memory-driven reasoning systems. Fine-tuned large language models (LLMs) using LoRA, QLoRA, and PEFT for real-world AI applications such as intelligent financial advisors and medical assistants.

Intern ML Engineer @ Hi-TechParks October 2025 – December 2025

Designed, developed, and deployed backend-centric AI/ML systems using Python, integrating models into production-grade services and APIs. Built and maintained scalable, modular AI backends including RAG and multi-agent workflows. Implemented end-to-end data and inference pipelines with optimised preprocessing, model serving, and performance-focused backend execution.

Portfolio