A Data Orchestrator and Certified Professional Data Engineer adept at harmonizing the realms of cloud computing, machine learning, and cutting-edge linguistics. With 4+ years of professional experience, I weave intricate data pipelines that traverse the landscapes of GCP, Azure, and AWS, harnessing the power of Python, SQL, Big Data, Spark, Machine Learning, Deep Learning, NLP, and Generative AI. Key Strengths: - Ability to work in ambiguous situations with unstructured problems. - Strong analytical skills with the ability to collect, organise, review significant amounts of information. - Experience using statistical computer languages Python to manipulate data and draw insights from large data sets. - Experience in fine-tuning large language models effortlessly for domain specific data. - Implement RAG Pipeline for Document Q&A tasks, Summarisation. - Expertise in some of the advanced machine learning techniques such as Clustering, Regression/Classification, Time Series Analysis, Network Analysis, Popular Deep Learning architectures and theory, simulation, scenario analysis. - Experience with machine learning on GCP Cloud. - Statistical thinking, Technical acumen, Team Player, Multi-modal communication skills to easily communicate complex ideas. Toolbox: - GCP (BigQuery, Dataflow, Data Fusion, Composer, IoT, TensorFlow, Dataproc), Azure, AWS, Postman, Airflow, MS-SQL, MySQL, Power BI, R, VS-Code Accomplishments: - 3X GCP Certified Professional Machine Learning Engineer - Transforming data into actionable foresight through predictive modelling Current Pursuit: Generative AI, Prompt Engineering, Large Language Models, Model Optimisation - Developed real-time AI-powered applications leveraging OpenAI API, Local LLMs with Python - Trained and evaluated cutting-edge LLMs, collaborated with ChatGPT, Claude, Gemini & many other open-source models. - Building Q&A systems with Knowledge Graphs and Large Language Models - Ongoing exploration of performance optimisation in RAG, Fine-tuning