Generative AI Engineer

11/2023 – 6/2024

» Built a multi-modal Retrieval-Augmented Generation (RAG) system for automated production of research. Integrated 5+ data sources, including web search and an in-house content farm. Deployed periodic reflection to ensure continual content relevance and improve accuracy by 20%.

» Led company-wide Artificial Intelligence (AI) strategy, defining product portfolio and 12-month roadmap. Directed AI implementations across departments, aligning technology adoption with business objectives.

Python, Data Science, Generative KI, Large Language Models, Natural Language Processing

1/2021 – 8/2023

» Led development of a high-performance Optical Character Recognition (OCR) pipeline capable of processing 1M+ multilingual documents across 30+ languages and 20+ formats. Architected an AWS/Azure multi-cloud solution, managing a cross-functional team of Data Scientists and MLOps engineers.

» Deployed a scalable Named Entity Recognition (NER) microservice for real-time data extraction, reducing manual document search time by 100+ hours annually. Implemented service with modular design for cross-departmental re-usability.

» Developed Topic Modelling and Search Engine tools for Research and Development (R&D), enabling the visualization of 10k+ papers and accelerating discovery of research.

» Built an in-house Applicant Tracking System (ATS) with NLP-powered analytics, 40% more customizable than standard tools, streamlining recruitment processes and providing critical insights for hiring decisions.

» Supervised a Natural Language Query (NLQ) thesis project, using state-of-the-art Graph Database interfaces, and bridging the gap between academic research and industry applications.

» Established company-wide Generative AI policies, driving adoption of best practices across teams and positioning the organization as an AI innovation leader.

SQL, Amazon Web Services (AWS), Data Science, Generative KI, Large Language Models, Natural Language Processing, Python

9/2020 – 11/2020

» Developed chatbot systems with user-personalized features, leveraging Natural Language Understanding (NLU) and Natural Language Generation (NLG) frameworks. Deployed Amazon Web Services (AWS) cloud infrastructure, CI/CD pipelines, and Docker containers, optimized for a high-velocity, agile start-up environment.

» Engaged in strategic product pitches to clients and contributed to financially informed decision-making.

Python, Amazon Web Services (AWS), Data Science, Natural Language Processing