BADDELA RAJU

AI Engineer | Data Scientist | Machine Learning Engineer

GitHub | LinkedIn | Email | Phone

[email protected]

+447887175084

London, UK

About

Highly analytical and detail-oriented AI Engineer with a robust foundation in machine learning, deep learning, and generative AI, specializing in developing and deploying end-to-end ML pipelines and LLM-based solutions. Proficient in Python, TensorFlow, and cloud platforms, I leverage MLOps practices and modern AI frameworks to deliver scalable, high-impact solutions that drive operational efficiency and enhance decision-making.

Work Experience

Assistant System Engineer

TCS

Jun 2024 - Sep 2024

Bangalore, Karnataka, IN

Led the development and maintenance of Python automation scripts, enhancing operational efficiency and data solution reliability within an Agile framework.

  • Developed and maintained Python automation scripts, processing over 50,000 records daily, streamlining workflows and boosting operational efficiency by 20%.
  • Designed and implemented a Pytest-based data validation framework, ensuring 100% test coverage and reducing manual QA efforts by 3 hours each week.
  • Collaborated within an 8-member Agile team to deliver scalable, production-ready data solutions on schedule, contributing to timely project completion.
  • Introduced robust error handling and logging mechanisms, improving system reliability and reducing debugging time by 30%.

Data Science Intern (Full Stack Data Science Bootcamp 2.0)

INEURON

Sep 2022 - Apr 2024

Remote

Executed end-to-end machine learning projects, from data collection to deployment, with a focus on model accuracy, MLOps, and production-ready API development.

  • Completed over 15 end-to-end ML projects, achieving an average model performance exceeding 85% across diverse applications.
  • Built and deployed machine learning models using Random Forest and XGBoost, increasing prediction accuracy by 25% through systematic hyperparameter tuning with GridSearchCV and RandomSearchCV.
  • Developed robust REST APIs using Flask, enabling seamless model serving in a production environment.
  • Implemented MLOps practices, including MLflow and DVC, decreasing model deployment time by 50% through automated pipelines.

Data Analytics Intern

KPMG

Jan 2022 - May 2022

London, England, UK

Analyzed customer data and developed segmentation models, providing actionable insights and improving reporting efficiency for marketing optimization.

  • Analyzed customer demographic data from over 5,000 records using Python and Excel, identifying key business insights to inform strategic decisions.
  • Built a customer segmentation model using K-means clustering, effectively identifying distinct customer groups for targeted marketing campaigns.
  • Created an interactive Tableau dashboard with 8 visualizations, reducing reporting time from 2 days to 2 hours.
  • Delivered actionable recommendations for marketing optimization, specifically impacting New South Wales and Victoria regions.

Education

Data Science

Roehampton University

Sep 2024 - Sep 2025

London, England, UK

Courses

  • Advanced Machine Learning
  • Deep Learning
  • Statistical Modelling
  • Big Data Analytics
  • AI Applications

Electronics and Communication

JNTUHCEJ University

7.89/10

Aug 2019 - Jun 2023

Hyderabad, Telangana, IN

Courses

  • Object-Oriented Programming
  • Databases
  • Data Structures and Algorithms
  • Artificial Intelligence
  • Image Processing

Certificates

Machine Learning Course

Stanford University

Dec 2023

Tableau Certification

Simplilearn

Dec 2022

Artificial Intelligence in Python

Great Learning

Dec 2022

Python Certification

Hacker Rank

Dec 2021

Projects

AI Trip Planner

A multi-agent AI system designed to generate personalized travel itineraries by leveraging LLMs and integrating real-time external APIs for comprehensive travel information.

Agentic AI Video Synthesizer

An autonomous system that transforms text queries into educational videos using Meta Llama LLM and a multi-agent architecture, focusing on efficiency and content accuracy.

Flight Fare Prediction

Developed and deployed an ML model for flight fare prediction using ensemble methods, featuring comprehensive feature engineering and a user-friendly web interface.

Lung Disease Prediction

A deep learning project utilizing a CNN model for chest X-ray image classification, incorporating data augmentation and transfer learning for enhanced accuracy and efficiency.

Skills

Programming Languages

  • Python
  • SQL

Machine Learning/Deep Learning

  • Scikit-Learn
  • TensorFlow
  • Keras
  • PyTorch
  • XGBoost
  • LightGBM
  • Supervised Learning
  • Unsupervised Learning
  • Neural Networks (ANN, CNN, RNN, LSTM, GRU)
  • Computer Vision (YOLO, RCNN)
  • NLP (BERT, GPT, Transformers)

Generative AI & LLM

  • LangChain
  • LangGraph
  • Llama Index
  • CrewAI
  • Autogen
  • Agno
  • Hugging Face
  • Vector Databases (Pinecone, Chroma DB, FAISS)
  • RAG Architecture
  • Prompt Engineering
  • Fine-Tuning
  • Agentic AI

Data Engineering

  • Pandas
  • NumPy
  • SciPy
  • Beautiful Soup
  • Apache Spark (basics)
  • ETL Pipelines
  • Data Preprocessing
  • Feature Engineering
  • A/B Testing
  • Hypothesis Testing

MLOps & DevOps

  • MLflow
  • DVC
  • Weights & Biases
  • Docker
  • Kubernetes (basics)
  • CI/CD
  • GitHub Actions
  • Airflow
  • Model Monitoring
  • Model Versioning

Cloud & Databases

  • AWS (EC2, S3, SageMaker)
  • Google Cloud (basics)
  • MySQL
  • PostgreSQL
  • MongoDB
  • Redis

Visualization & Tools

  • Tableau
  • Power BI
  • Excel
  • Matplotlib
  • Seaborn
  • Plotly
  • Streamlit
  • Flask
  • FastAPI

Methodologies

  • Agile
  • Git
  • JIRA
  • Test-Driven Development