Devanshu Khurma
Applied Machine Learning Scientist II at TD Bank Group and Computer Science M.S. graduate from the University of Texas at Austin (4.0 GPA). Expert at architecting Agentic AI, custom Generative AI workflows, and cost-efficient cloud systems that deliver documented enterprise savings of over CA$28MM+ annually.
About Me
I am an AI/ML Engineer and Solutions Architect specializing in translating complex business challenges into production-ready, highly scalable machine learning ecosystems. My background sits at the intersection of advanced algorithm development, high-efficiency system design, and strategic business-value generation.
At TD Bank Group, I serve as a primary technical SME, architecting and deploying end-to-end Agentic AI systems utilizing Large Language Models (LLMs) and Vision Language Models (VLMs) on Azure Databricks. My work has reduced underwriting turnaround times from 15 hours to 15 minutes, generating CA$15 million in annual savings and resulting in 4 filed patents.
I hold a Master of Science in Computer Science from the University of Texas at Austin (4.0 GPA) and a Master of Management in Analytics from McGill University (3.9 GPA, Dean's List). This blend of deep computer science knowledge and quantitative business analytics enables me to build technically elegant solutions that scale seamlessly while optimizing compute cost and infrastructure pipelines.
Technical Expertise
Work History
Toronto Dominion Bank Group
September 2022 – Present | Toronto, ON
Applied Machine Learning Scientist II Current Role
February 2025 – Present
Architected and deployed Agentic AI solutions on Azure Databricks for automated mortgage underwriting, cutting document turnaround processing by 98% and driving CA$15 million in annual savings.
Conceptualized, drafted, and filed 4 distinct machine learning patents within 12 months, pioneering novel architectures in enterprise AI automation.
Fine-tuned a RAG knowledge management system utilizing Hugging Face PEFT (LoRA) and custom instruction-response datasets, significantly optimizing context retrieval speed while minimizing inference-level compute costs.
Spearheaded organization-wide AI literacy by organizing and leading GitHub Copilot Bootcamps and technical workshops, accelerating agile software development across engineering units.
Data Scientist II
September 2022 – February 2025
Architected a deep learning based anomaly detection engine to identify and mitigate high-risk behavioral trends, generating CA$13.5M in value.
Designed and maintained robust end-to-end Responsible AI pipelines to ensure fairness, interpretability, and compliance with strict federal bank regulations.
Served as the primary technical subject matter expert (SME) to translate complex business requirements into scalable workflow architectures for data engineering teams.
Led key data governance integrations to resolve data inconsistencies following massive cloud migrations, ensuring high compliance and zero business disruption.
Machine Learning Engineer @ Laps
August 2021 – September 2022 | Montreal, QC
Optimized large scale compute infrastructure using GCP BigQuery and AWS SageMaker, achieving a 200x pipeline acceleration and saving CA$18K annually.
Developed and deployed a real-time intent detection chatbot utilizing custom word embeddings, cutting support agents' workload by 28% and boosting client response efficiency.
Consulted on and built a highly concurrent recommender API using AWS Personalize, integrating modern CI/CD DevOps workflows to ensure seamless deployments.
Co-authored architectural pitch decks demonstrating the viability of core machine learning solutions to stakeholders, directly supporting successful funding campaigns.
Data Scientist - Go-to-Market Operations @ Brother International
July 2020 – August 2021 | Montreal, QC
Refactored and optimized complex logistics ETL pipelines in Scala, eliminating redundant queries and saving over 200+ hours in manual tracking operations annually.
Designed and launched a custom time-series forecasting model, achieving an 87% accuracy rating (MAPE) and delivering 15% Forecast Value Added over baseline legacy projections.
Translated historical freight and supply data into rich, interactive business dashboards, enabling Go-to-Market operations teams to refine regional logistics operations.
Business Intelligence Consultant @ Canadian National Institute for the Blind Foundation
June 2020 – August 2020 | Montreal, Canada
Identified and defined key performance indicators (KPIs) to evaluate user interaction and success across all of **CNIB's online courses**.
Built a robust **data processing pipeline** in Python and SQL to aggregate and combine raw input from multiple independent database sources.
Developed and launched an interactive **PowerBI dashboard** to efficiently track educational KPIs, spot operational anomalies, and automate reports, saving 12 hours of manual analysis each month.
Analytics Consultant (Pro-Bono) @ Thinkr Consulting
January 2020 – May 2020 | Montreal, Canada
Conducted **pro-bono consulting for Mkono**, a Kenyan microfinance non-profit organization supporting entrepreneurs with affordable loans and mentorship.
Created and deployed a robust **credit scorecard-based machine learning model** to evaluate microfinance loan viability for local entrepreneurs.
Translated complex, multi-dimensional customer behavioral profiles into a highly interpretable and actionable **point-based credit ranking system** for loan officers.
Solutions Architect - Analytics Consulting Project @ Nestle Canada
October 2019 – June 2020 | Toronto/Montreal, Canada
Designed and implemented a statistical pipeline to **generate highly realistic indicative data**, closely simulating complex real-world retail and supply-chain scenarios.
Created and mapped the comprehensive **process and solution architecture** to identify, segment, and predict consumer behavioral patterns across retail platforms.
Built, validated, and successfully **deployed end-to-end machine learning models on Google Cloud Platform (GCP)** to track shopper trend dynamics.
Software Engineer Intern @ Samsung Research and Development Institute
May 2018 – July 2018 | Bangalore, India
Implemented unsupervised machine learning techniques to segment user bases based on activity levels, delivering insights to product design teams.
Utilized Agile methodologies in a fast-paced development ecosystem to achieve key project milestones strictly on schedule.
Gained hands-on expertise with Git version control, actively participating in team code reviews and providing constructive architectural feedback.
Education
University of Texas at Austin
Master of Science in Computer Science
Focused on advanced machine learning algorithms, deep learning neural networks, Generative AI, scalable cloud computing systems, and computational theory.
McGill University
Master of Management in Analytics
Dean’s List. Specialised in machine learning business applications, linear programming, mathematical optimization, advanced statistical forecasting, and database engineering.
Delhi Technological University
Bachelor of Engineering in Computer Science
Completed core coursework in data structures, design and analysis of algorithms, database systems, object-oriented software engineering, and computational mathematics.
Featured Projects
Agentic Mortgage Underwriter
An advanced enterprise-level Agentic AI solution utilizing Vision Language Models (VLMs) and multi-agent frameworks (LangGraph) running on Azure Databricks. Automates complex mortgage document extraction and verification steps, reducing manual cycle times from 15 hours to 15 minutes while generating CA$15MM in audited annual savings.
Read Work Details
Responsible AI Anomaly Engine
A custom deep learning pipeline engineered to detect behavioral and operational risk vectors across transaction systems. Incorporated strict Responsible AI metrics and bias evaluation algorithms, improving model precision by 115%, recall by 23%, and safeguarding financial operations worth CA$13.5MM in value.
Read Work DetailsOther Engineering Work
PEFT Knowledge RAG
Fine-tuned transformer models using LoRA on custom instructions to power a high-precision knowledge synthesis workspace for client operations, minimizing compute constraints.
GPT-3 News Aggregator
Developed a news aggregation application leveraging GPT-3 for abstractive text summarization of articles. Implemented automated scraping, content summarization, and responsive delivery.
Regime: Fitness App
Full-stack Android app with a well-structured Firestore database, leaderboards, social feeds, and Kotlin Coroutines/Flow for smooth asynchronous data fetching. Evaluated via unit & integration tests.
Scalable Recommender API
Consulted on and launched a real-time recommender engine utilizing AWS Personalize, optimized to resolve concurrent user demands under tight service latency requirements.
Scala ETL Logistics Pipeline
Re-engineered legacy warehouse extraction tools into highly efficient, modular Spark operations in Scala, mitigating post-cloud discrepancies and reducing manual runtime tracking.
Interests & Pursuits
Running
Training consistently for full and half marathons, with a personal marathon best of 3:17. I also love trail running, with my largest challenge to date being a grueling 51k trail race.
Digital Photography
Capturing urban landscapes, architecture, and wilderness trails. I enjoy exploring composition, light contrast, and post-processing techniques to document unique visual perspectives.
Chess
Fascinated by geometric puzzle patterns, structural positional advantages, and endgame calculations. I enjoy playing rapid chess games and working through tactical scenarios online.
Tennis
Active singles player in amateur community leagues. I enjoy the fast-paced coordination, adjusting ball spin and court angles under match conditions, and continuous technical refinement.
Language Learning
Fascinated by semantic structures, phonetics, and local cultural contexts. I hold a JLPT N5 certification and am currently studying towards the N4 level. I am particularly interested in exploring the grammars of English, Sanskrit, and Japanese.
Travel
Exploring historical architectures, trying local food markets, and hiking wilderness trails across national parks. Travel allows me to step back, experience new cultures, and gain fresh perspectives.
Let's Connect
Whether you are looking to hire a business-impact-driven AI/ML Engineer, an enterprise-level Solutions Architect, or need engineering consultation on advanced Agentic AI deployment, my inbox is always open.