Toronto, Ontario, Canada
- Expert in machine learning, large language models (LLMs), generative AI, and data science with 15+ years of experience transitioning rapid prototypes into production-grade applications that drive measurable ROI. - Pioneering the development of next-generation, autonomous agentic systems and multi-agent workflows for enterprise clients, utilizing advanced frameworks like Google's Agent Development Kit (ADK) and LangGraph to deliver secure, scalable, and high-performance solutions. - Top GenAI expert who architects advanced solutions and leads teams, actively co-building with client engineering teams to instill development best practices, upskill talent, and ensure high end-user adoption. - Expert in Software Development, Object-Oriented design, and cloud architecture, bridging the enterprise gap by coding the connective tissue between advanced AI products, live infrastructure, APIs, and big data silos using Agile execution. - Successful track record of delivering Data and AI solutions on budget and on time for Fortune-500 clients across diverse industries (mining, energy, finance, transport, health, non-profit), ensuring systems meet rigorous requirements for accuracy, safety, and latency. - Recognized thought leader with publications in natural language processing (NLP), machine learning, and big data, capable of identifying technical field patterns and converting them into reusable enterprise modules.
As a Generative AI Blackbelt at Google, I am dedicated to assisting some of Google Cloud's most prominent customers in their business transformation. My primary focus is on evaluating and implementing AI products and services, with the focus on Generative AI, offered by Google Cloud.
As the AI/Data Science Lead, I was focused on building impactful digital experiences for leading global brands. By collaborating with key partners Accenture and Microsoft, we deliver industry-leading solutions to organizations seeking scalable business solutions.
Worked on image processing in seismic data. My work involved various applications of deep learning, computer vision, feature extraction, image processing, pattern recognition, and machine learning in general.
With a group of 4, successfully contributed to developing the full content for Python course for a class with 900 students.
Was teaching assistant for more than 15 courses in the field of software engineering including both graduate and undergraduate programs. Courses: Software Testing; Principles of Software Development (2 times); Computer Organization, Programming Fundamentals; Dependability and Reliability of Software Systems, Computing for Engineers (2 times, one time as TA Coordinator); Programming Fundamentals for Software and Computer; Software Testing, Reliability and Quality (3 times); Software Design & Architecture I (2 times)(MEng students); Principles of Software Development I (MEng students); MEng Project I