Hello, I'm

Jacob Binu Mancherikalam

MLOps & AI Engineer

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About Me

Jacob Binu

MLOps & AI Engineer specializing in the complete lifecycle of scalable intelligent systems. I combine expertise in the development and deployment of robust production-ready Machine Learning, LLM, and Agentic models on AWS, Azure, and GCP using Docker, Kubernetes, and CI/CD.

I am proficient in bridging the gap between data science and application deployment by architecting full-stack interfaces (React, Flask) and optimized RESTful APIs. My expertise ranges from training deep learning models to orchestrating production deployments on Cloud environments. I am passionate about building automated, scalable pipelines that deliver high-performance AI solutions with seamless user experiences.

Technical Skills

Languages

Python C++ Java C SQL Bash/Shell MATLAB

AI & GenAI

PyTorch TensorFlow Keras Scikit-learn OpenCV Hugging Face LangChain LangGraph RAG LLMs (GPT, Llama)

Deep Learning

CNNs RNNs LSTMs Transformers CUDA/cuDNN

MLOps & Cloud

AWS Azure GCP Docker Kubernetes Azure DevOps CI/CD Databricks MLflow Git

Data Engineering

PySpark Pandas NumPy Kafka Redis MongoDB MySQL SQLite AWS Glue

Full Stack

React Flask Django HTML5 CSS3 JavaScript RESTful APIs

Work Experience

MLOps Engineer

Coventry Building Society, Coventry

January 2025 - Present

  • Establish comprehensive MLOps best practices, creating automated workflows for model versioning, reproducibility, and CI/CD deployment.
  • Deploy critical Credit Risk models (IRB & IFRS9) within the analytics platform using Python.
  • Engineer serverless ETL pipelines using AWS Glue, automating complex data manipulation and loading into Amazon Redshift.
  • Architect and maintain scalable data frameworks using Python, PySpark, and SAS.
  • Spearhead Proof-of-Value initiatives for emerging ML platforms.

IT Engineer

Tata Motors Design Tech Centre, Coventry

August 2022 - August 2023

  • Engineered an autonomous OS deployment pipeline for Windows 11, reducing manual intervention by 80%.
  • Developed robust automation scripts using PowerShell and Bash to streamline automation.
  • Optimized IT incident response workflows, driving the ticket closure rate from 50% to 100% within six months.

Featured Projects

Knowledge Graph RAG System

Implementation of a GraphRAG system using a Flask application with the Ollama API and locally built models, leveraging graph-based structures for advanced query retrieval.

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End-to-end MLOps with Databricks

A complete, end-to-end MLOps architecture built on the Databricks platform. Features data preparation, model training with MLflow, registration, and serving.

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Context-Aware Chatbot (RAG)

A context-aware chatbot built using a Retrieval-Augmented Generation (RAG) framework, leveraging state-of-the-art LLMs like OpenAI’s GPT and Meta’s Llama.

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Toxicity Classification Pipeline

A complete Python solution for classifying mushrooms as edible or poisonous using various ML algorithms, transformed into a reliable, production-ready system via MLOps.

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CNN Plant Disease Classification

A production-ready MLOps system for classifying plant diseases using CNNs. Transforms a research notebook into a scalable, reproducible, and automated ML pipeline.

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Twitter Sentiment Analysis

A production-ready Flask application that analyses real-time tweets from financial influencers using advanced NLP sentiment analysis to track market sentiment.

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Education

BSc Computer Science with AI

Coventry University

2021 - 2024

Grade: First Class Honors

Key Modules: Artificial Neural Networks & Intelligent Agents, Machine Learning, Advanced Algorithms.

Certifications

Cisco

CCNA: Enterprise Networking, Security, and Automation (2023)

Google Cloud

Generative AI: Working with Large Language Models (2023)

Get In Touch

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