DUNCAN McKINNON

AI Engineer

Seattle, WA
duncankmckinnon.com
duncankmckinnon
duncankmckinnon

PROFESSIONAL SUMMARY

AI Engineer with comprehensive experience spanning software engineering, data science, MLOps, and LLM applications. Currently working with enterprise teams to build robust, scalable agentic systems and LLM workflows for production environments, with prior experience delivering machine learning infrastructure, reinforcement learning solutions, and recommendation systems driving $40M+ in revenue.

PROFESSIONAL EXPERIENCE

Arize AI
November 2023 – Present | Seattle, WA
Forward Deployed AI Engineer
March 2025 – Present
  • Develop safe, scalable LLM workflows and agent systems for production use cases in public and private sectors as the first field AI engineer
  • Partner with enterprise AI and ML infrastructure teams to solve complex challenges in AI evaluation, MLOps, production workflow automation, observability, and monitoring
  • Develop and maintain public Python SDK that accelerates integration of observability and evaluation tools in production environments
  • Create frameworks and reusable project templates to increase velocity in customer engagements, collaborating across engineering, product, solutions, and GTM teams
AI Solutions Engineer
November 2023 – March 2025
  • Built MLOps observability integrations for real-time and batch workflows on the Instacart Griffin ML platform
  • Collaborated with leadership and data science teams across 15+ enterprise and public sector accounts to integrate model inferences and identify actionable, value-driving insights
  • Instrumented LLM tracing and monitoring for enterprise clients, providing guidance on GenAI production evaluations, guardrails, prompting, observability, and experimentation workflows
Wayfair
Machine Learning Engineer 2
March 2022 – November 2023 | Seattle, WA
  • Led engineering team in implementing solutions to reduce latency in real-time machine learning systems
  • Designed and tested customer recommendation systems driving over $40M/year in revenue
  • Stress tested GCP feature serving platform with various models, gaining buy-in for recommended improvements to online ML systems
  • Developed MLflow model deployment and REST service tools that reduced time to productionalize models from days to hours
  • Implemented monitoring capabilities to track machine learning performance and data drift using Arize platform
Microsoft (via Neal Analytics)
Data Scientist
July 2020 – March 2022 | Seattle, WA
  • Led data science consulting team in developing resource allocation forecast models and pipelines that reduced infrastructure failure response times by 5-7 minutes for major national utility provider
  • Delivered end-to-end deep reinforcement learning solution for international mining company, developing orchestration framework to manage simulation, training, assessment, and visualization
  • Built web API to generate strategic planning reports using Python, AnyLogic, Azure, Flask, Docker, and Microsoft Project Bonsai
  • Led implementation of scalable end-to-end retail demand forecasting solutions for multiple clients using Azure Databricks, Apache Spark, and Prophet
AT&T
January 2018 – July 2020 | Seattle, WA
Software Engineer 2
June 2019 – July 2020
  • Designed, developed, and deployed personalization services supporting 20+ million unique requests daily across 30+ customer webpages on 3 independent applications
  • Led research and presented comparative cloud architecture strategies for migrating on-premise services to AWS and Azure
  • Researched and implemented online machine learning system capturing real-time importance rankings to improve content recommendations
Software Engineer 1
January 2018 – June 2019
  • Created microservices for configurable content recommendation system
  • Led creation of application monitoring systems to flag malicious traffic, identify service inefficiencies, and present performance results to business leadership

EDUCATION

Master of Science in Applied & Computational Mathematics & Statistics (Data Science)
University of Notre Dame
2018 – 2020
Bachelor of Science in Computer Engineering
University of Washington Bothell
2014 – 2017
Minors: Physics, Mathematics

PUBLICATIONS

  • Great Books for AI Engineering (Towards Data Science, 2025)
  • Achieving Self-Service Onboarding for MLOps Tooling (Wayfair Tech Blog, 2023)
  • Great Books for Data Science 2 (Towards Data Science, 2021)

CERTIFICATIONS

  • Reinforcement Learning Specialization (University of Alberta, 2021)
  • Generative Adversarial Networks Specialization (DeepLearning.AI, 2021)
  • Natural Language Processing Specialization (DeepLearning.AI, 2020)
  • Deep Learning Specialization (DeepLearning.AI, 2018)