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Senior Machine Learning Engineer | Google Cloud Architect | Available Full-Time | Part-Time PhD @ City St Georges | MSc in AI | Gen AI (Gemini) | Industrial Opt | Stanford Alumnus
Industrial intelligence requires a seamless integration of scalable data foundations, mathematical rigour, and governed cognitive reasoning. As a Senior ML Engineer and Google Professional Cloud Architect, my primary focus is building "Production-Ready AI." I am currently pursuing a part-time PhD at City St Georges University—structured specifically to allow for immediate, full-time industry roles. My background in Electrical Engineering and Physics provides a unique perspective on bridging the "Sim-to-Real" gap, transforming theoretical models into high-integrity industrial systems. Professional Pillars: Cloud Architecture & Data Engineering: Designing resilient pipelines for processing large datasets via batch and real-time streaming. Leveraging my Google Cloud Architect expertise, I focus on large-scale ETL design and modern, scalable data architectures to ensure industrial data is robust and performant. Governed Gen AI & Multi-Agent Systems: Developing enterprise-grade systems utilizing Gemini. I architect multi-agent systems designed for complex planning and execution, strictly following Google’s Agent-Building recommendations and Responsible AI principles through rigorous evaluation and agentic guardrails. Scheduling Theory, Algorithms, and Systems (Part-Time PhD Research): Pursuing research in the design, analysis, and implementation of advanced scheduling algorithms. My focus is on exploring foundational theories and building robust system architectures to solve complex optimization problems for real-world industrial application.
St George's, University of London (for students and alumni)
Doctor of Philosophy - PhD, AI & Optimization
February 1, 2026 – February 1, 2033
Toronto Metropolitan University
Master's degree, Artificial Intelligence
March 1, 2021 – March 1, 2021
Toronto Metropolitan University
Certificate in Big Data and Predictive Analytics, Datascience
January 1, 2014 – January 1, 2015
The University of the West Indies, Mona
Master's degree, Electrical and Electronics Engineering
January 1, 2001 – January 1, 2005
City St George's, University of London
PhD Researcher (Industrial AI & Optimization)
February 1, 2026 – Present
Toronto, Ontario, Canada · Remote
York University
Lead Course Instructor
January 1, 2018 – September 1, 2018
Greater Toronto Area, Canada
York University
Course Developer
January 1, 2018 – August 1, 2018
Greater Toronto Area, Canada
RBC
Senior Machine Learning Engineer
February 1, 2016 – March 1, 2025
Toronto, Ontario, Canada · Hybrid
LocationGenius
Senior Data Scientist
July 1, 2015 – January 1, 2016
Greater Toronto Area, Canada
Ryerson University
Big Data and Predictive Data Analytics Assistant Instructor
May 1, 2015 – May 1, 2016
Ryerson University
Software Engineer
October 1, 2014 – April 1, 2015
Exterbox
Technical Cofounder
January 1, 2007 – January 1, 2013
Jamaica
Deep Learning
University of San Francisco
June 24, 2026 – Present
Image Denoising Using AutoEncoders in Keras and Python
Coursera
June 24, 2026 – Present
DeepLearning.AI TensorFlow Developer Specialization
Coursera
June 24, 2026 – Present
TensorFlow: Data and Deployment by DeepLearning.AI
Coursera
June 24, 2026 – Present
App Deployment, Debugging, and Performance
Coursera
June 24, 2026 – Present
Developing Applications with Google Cloud Platform Specialization
Coursera
June 24, 2026 – Present
Securing and Integrating Components of your Application
Coursera
June 24, 2026 – Present
Getting Started With Application Development
Coursera
June 24, 2026 – Present
Google Cloud Platform Fundamentals: Core Infrastructure
Coursera
June 24, 2026 – Present
Natural Language Processing With Deep Learning
Stanford Online
June 24, 2026 – Present
DevOps for Data Scientists
June 24, 2026 – Present
Kubernetes the Hard Way
Linux Academy
June 24, 2026 – Present
edX Honor Code Certificate for Introduction to Big Data with Apache Spark
edX
June 24, 2026 – Present
edX Honor Code Certificate for Scalable Machine Learning
edX
June 24, 2026 – Present
Programming Cloud Services for Android Handheld Systems
Coursera Course Certificates
June 24, 2026 – Present
Pattern-Oriented Software Architectures: Programming Mobile Services for Android Handheld Systems
Coursera Course Certificates
June 24, 2026 – Present
Programming Mobile Applications for Android Handheld Systems
Coursera Course Certificates
June 24, 2026 – Present
Preparing for Google Cloud Certification: Machine Learning Engineer
Google Cloud
June 24, 2026 – Present
Generative AI Leader Certification
June 24, 2026 – Present
Gemini Certified Educator
Google for Education
June 24, 2026 – Present
Build, Train and Deploy ML Models with Keras on Google Cloud
Google Cloud
June 24, 2026 – Present
Production Machine Learning Systems
Google Cloud
June 24, 2026 – Present
Machine Learning in the Enterprise
Google Cloud
June 24, 2026 – Present
Feature Engineering
Google Cloud
June 24, 2026 – Present
ML Pipelines on Google Cloud
Google Cloud
June 24, 2026 – Present
Machine Learning on Google Cloud Specialization
Google Cloud
June 24, 2026 – Present
Professional Cloud Architect Certification
June 24, 2026 – Present
Generative AI at the Edge: Design, Deploy, and Optimize Generative AI Models
June 24, 2026 – Present
Introduction to Machine Learning with TensorFlow
Udacity
June 24, 2026 – Present
Academy Accreditation - Generative AI Fundamentals
Databricks
June 24, 2026 – Present
AI Pair Programming with GitHub Copilot
June 24, 2026 – Present
Introducing Semantic Kernel: Building AI-Based Apps
June 24, 2026 – Present
Doubling Your Productivity
June 24, 2026 – Present
XCS221 - Artificial Intelligence: Principles and Techniques
Stanford Online
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's diverse experience across industry (finance, startups), academia (teaching, research), and various technical roles (ML Engineer, Data Scientist, Software Engineer, Technical Cofounder) suggests adaptability and a broad perspective. The ongoing PhD and numerous certifications in AI/ML and cloud technologies demonstrate a strong commitment to continuous learning and staying current with industry trends, which aligns well with a culture of innovation and growth. The experience in regulated environments (RBC) indicates an understanding of structured processes and compliance.
Soft Skills & Operational Fit
The candidate's resume highlights experience in leading teams (Technical Cofounder), collaborating with cross-functional teams (RBC), and providing mentorship and training (Ryerson University, York University). These indicate strong leadership, collaboration, and communication skills essential for a senior role. The PhD research on 'Agentic Research Workflows' and 'Cyber-Physical Digital Twins' suggests a proactive and innovative approach to problem-solving. The focus on 'Google’s Responsible AI guidelines' indicates an awareness of ethical considerations in AI development.