Microsoft Azure-certified Data specialist. A technologist with several years of versatile experience in: AI/ML develpoment and deployment, Data Engineering ETL, Data Analysis and reporting, across various sectors, including finance, insurance, and energy.
🎓 Robotics (AI) Postgraduate at King's College London
🎓 Graduated with First Class Honours in Artificial Intelligence from the University of Kent
🏅 UGOTY AI & Robotics Finalist 2023
- Mentored and led senior, mid-level, and junior developers from industry clients including Google, Barclays, Palantir Technologies, and Thales Group to build high-quality, end-to-end data solutions.
- Drove business impact for clients by delivering MLOps and LLMOps solutions, combining industry best practices with hands-on senior engineering, pair programming, and development of AI systems across data engineering, RAG, and generative AI applications.
- Advised stakeholders on AI strategy, including roadmaps, risk mitigation, and ethical AI governance frameworks.
- Authored internal technical blogs and delivered workshops on scalable, multimodal architectures.
- AI Development Company for clients
- Examples include the Development of 'Research Wizard' for AI based document analysis, presentation, essay and video reel automation with applications in robotic task planning and data processing.
- Development of front end and backend services utilising open source LLMS, FAISS, ONNX, Indexes, Gemini and OpenAI endpoints.
- Development of E-commerce AI enabled cross listing platform utilising RAG & Generative AI to increase sales for customers.
- Developed a human-like grasping robot with a YOLOV11 computer vision model and autonomous pose detection to capturing varying space debris.
- Presented at a London conference to 200+ industry experts, praised for its real-world potential in orbital debris removal.
- A space debris removal system developed in simulation using NVIDIA Isaac Sim, a YOLOV11 computer vision model and ROS2.
- Designed to simulate a multimodal robotic collector operating in orbit
- Computer Vision Model autonomously detected varying debris in a space simulated environment.
- Led the ML analysis of Driver Insurance Claims accross the UK
- Created an end to end pipeline to cleansed and processed 6 million rows of claims data using PySpark on Databricks
- Developed ML in house models to predict customer risk profiles before applying unique pricing to individual customers
- Saved several millions through price optimisation
- Led the migration of Oil Shipping Vessel Data through ETL to Azure Cloud Platform.
- Created a robust set of daily pipelines processing millions of records on Azure Analytics with PySpark.;
- Generated SQL-based views and PowerBI Reports before applying ML to optimise shipping operations
- Saved several millions of dollars in shipping trips
- Learnt about model maintenance and development using Google Cloud
- Gained exposure to enterprise-level data infrastructure, cloud computing, and AI pipelines
- Azure Fundamentals (AZ-900)
- Azure AI Fundamentals (AI-900)
- Greater Learning Academy: Python, Seaborn, Matplotlib, Google Colab
- MachineLearning.org.in: ChatGPT
- Academic Excellence Scholarship — University of Kent