AI / ML Specialization

AI Systems & Machine Learning

Designing, training, and deploying end-to-end intelligent systems — from LLM fine-tuning and RAG pipelines to multimodal CLIP search and graph representation learning.

Specializations

Core Focus Areas

🧠

LLM Engineering

Prompt engineering, instruction tuning, evaluation frameworks, and building production LLM pipelines with structured output and tool use.

Qwen2.5GPT-4oMistralStructured OutputEvalsMLflow
🔍

RAG Systems

Retrieval-augmented generation: document ingestion, chunking strategies, dense retrieval with sentence-transformers, hybrid search, and grounded generation with citations.

sentence-transformersFAISSBAAI/bge-small-en-v1.5LangChainCitations
⚙️

Fine-Tuning

End-to-end fine-tuning pipeline for Qwen2.5 LLMs: dataset engineering, SFT/LoRA/QLoRA training via mentorai-cli, evaluation (ROUGE/BLEU/BERTScore/LLM-as-Judge), and deployment as the model backing MentorAI.

QLoRALoRAPEFTTRLBitsAndBytesQwen2.5MLflow
👁️

Multimodal AI

End-to-end multimodal product search engine: CLIP (ViT-B/32) embeddings + FAISS IndexFlatIP across 145,050 products, with zero-shot tagging, weighted fusion (60/40 image/text), offline recommendations, and Kafka-tracked search events feeding Airflow-scheduled daily reindex.

CLIP (ViT-B/32)FAISSFastAPIKafkaAirflowZero-Shot TaggingStreamlit
📊

Machine Learning

Supervised and unsupervised ML for classification, regression, risk scoring, anomaly detection, graph-based learning, and reinforcement learning. Production deployment with MLOps practices.

Scikit-learnPyTorchNode2VecMLflowFinBERT
Architecture

AI System Pipelines

Concrete architectural patterns used across production AI and ML projects.

RAG Pipeline (MentorAI)

01

Documents

PDF, Markdown, Code

02

Chunking

512 tokens + overlap

03

Embeddings

BAAI/bge-small-en-v1.5

04

Vector Store

FAISS IndexFlatIP

05

Retrieval

Top-K dense search

06

LLM + Context

Qwen2.5 (QLoRA fine-tuned)

07

Grounded Response

With citations

MentorAI Fine-Tuning Pipeline (LLM Fine-Tuning Framework)

01

Knowledge Units

Domain source material

02

Dataset Engineering

Alpaca / ChatML / ShareGPT formats

03

Tokenization

Reusable pipeline

04

Training

SFT → LoRA → QLoRA (4-bit)

05

Evaluation

ROUGE, BLEU, BERTScore, LLM-as-Judge

06

Model Export

Adapter merge, Safetensors

07

Inference API

FastAPI, feeds MentorAI

VisualMind Search Pipeline (VisualMind)

01

Query

Image, text, or both

02

CLIP Encoder

ViT-B/32, 512D embedding

03

Multimodal Fusion

Weighted average (60/40 image/text)

04

FAISS IndexFlatIP

145,050 vectors, exact search

05

Results + Tags

Zero-shot category/color/style

06

Kafka Events

Search telemetry

07

Airflow Rebuild

Daily index + recommendation refresh

Selected Work

Featured AI Projects

Multimodal AICompleted

VisualMind

Traditional text-based product search misses visual similarity — users can't find what they're looking for with words alone.

PythonCLIPFAISSFastAPIKafka
Explore Case Study
RAG PlatformCompleted

MentorAI

Technical learners waste hours searching docs and tutorials when they need a specific, contextual answer grounded in their actual study material.

PythonNestJSNext.jsFastAPIFAISS
Explore Case Study
LLM EngineeringCompleted

MentorAI Fine-Tuning Pipeline

No reusable, production-ready pipeline exists for fine-tuning open-source LLMs on domain-specific data — every project starts from scratch.

PythonPyTorchQwen2.5PEFTTRL
Explore Case Study
Graph Machine LearningCompleted

Email EU Graph Platform

Organisational communication patterns are invisible — email data contains rich relational structure that standard tools cannot exploit.

Next.jsNestJSFastAPIPythonNetworkX
Explore Case Study
Statistical Data ScienceCompleted

Plant Biology Statistical Analytics Pipeline

Biological research experiments feature complex multivariate interactions across treatments and genotypes, requiring rigorous, reproducible statistical modeling to extract publication-grade insights.

PythonPandasNumPyScikit-learnSciPy
Explore Case Study
AI Email AutomationCompleted

Smart Email Assistant

Repetitive email work — classification, prioritisation, drafting standard replies — consumes hours that could be spent on meaningful work.

PythonDistilBERTT5-smallFAISSFastAPI
Explore Case Study
Financial Risk Research & SimulationIn Progress

Sentinel-AI

Financial risk analysis requires integrating heterogeneous data sources — market OHLCV data, news sentiment, chart patterns, and regulatory filings — into a unified, explainable risk scoring system.

PythonLightGBMFinBERTPyTorchLangChain
Explore Case Study
Toolbox

AI & ML Toolchain

Python

Python

Core ML & pipeline development

PyTorch

PyTorch

Deep learning & fine-tuning

HuggingFace

HuggingFace

Transformers, PEFT, TRL

FAISS

FAISS

Dense vector retrieval

LangChain

LangChain

RAG pipelines & LLM orchestration

MLflow

MLflow

Experiment tracking & model registry

Scikit-learn

Scikit-learn

Classical ML & feature engineering

Pandas

Pandas

Data manipulation & analysis

NumPy

NumPy

High-performance vector operations

Kafka

Kafka

Event streaming pipeline

Airflow

Airflow

Workflow orchestration & scheduling

Docker

Docker

Containerized deployment

06 Certified AI/ML Specializations

Stanford University, DeepLearning.AI, and DataCamp verified credentials.

Machine Learning SpecializationAdvanced Learning AlgorithmsSupervised Machine Learning
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