Mason Macklem

Building AI that
actually ships.

I'm Mason — an AI leader and researcher, building ML Systems specializing in Video and Multimodal Intelligence.
10+ years building teams and products in Critical Infrastructure Monitoring, and 5+ years building teams and products in Online Safety and Security, I build ML-driven teams and systems that go from whiteboard to production, from idea to reality.

12+

years leading
technical teams

years in online
safety & security

10+

years in critical
infrastructure

PhD

Computer Science
Dalhousie

The short version

I've spent most of my career at the intersection of video, machine learning, and cloud infrastructure — first building the plumbing, then building the brains on top of it. I genuinely like the hard problems: multimodal pipelines, agentic systems, production ML at scale.

I care about mentorship as much as I care about architecture. Folks I've worked with have gone on to Ivy League PhDs, founded VC-backed startups, and joined teams at Google, Microsoft, and Amazon. That stuff matters to me.

Outside of work I'm active in the Okanagan tech community — co-organizing meetups, bridging local industry with UBCO faculty, and generally trying to make the Kelowna tech scene a bit better than I found it.

What I've been building

Recent production work across video intelligence, agentic systems, and generative AI.

🎬

Multimodal Video Pipelines

Automated ad safety, metadata labeling, theme detection, and captioning (with translation) for a family streaming platform.

🤖

Autonomous Agent Systems

Deployed agents to monitor infrastructure health and predict production risk. Also rolled out org-wide AI assistants for self-serve KPI access.

🔒

Content Safety & Moderation

Human-in-the-loop labeling workflows with active feedback loops. Content scoring based on viewer sentiment for recommendations.

🧪

Research to Production

From RL and optimization research (postdoc, PhD) to shipping real systems. I understand both sides of the research–engineering divide.

⚡

Generative AI Integration

Hands-on with OpenAI, Anthropic, open-weight LLMs, speech/video synthesis, and multimodal media models in production environments.

☁️

AWS ML Stack

Deep experience with SageMaker, Bedrock, AgentCore, Step Functions, Lambda, and CloudWatch AI Investigations.

Where I've worked

Aug 2023 – Feb 2026

Director, Research & Machine Learning

Kidoodle.TV

Built and led a cross-functional ML team delivering production video intelligence across ad safety, streaming analytics, and generative media
Designed automated multimodal pipelines for ad safety and metadata labeling on a family-centric streaming platform
Deployed autonomous agents for infrastructure monitoring and production risk prediction
Rolled out org-wide AI assistants for self-serve KPI access; led the company's AI-first culture shift
Owned ML architecture and communicated tradeoffs to execs and technical stakeholders

AWS Sagemaker Bedrock AgentCore OpenAI Anthropic Multimodal LLMs Step Functions Lambda

Jan 2023 – Aug 2023

Senior Researcher

Kidoodle.TV

Jan 2022 – Nov 2022

Senior Researcher

Oooh

Architected cross-modal integrations: text-to-speech, speech-to-text, text-to-image into video pipelines
Built content-based video recommendation and moderation systems
Developed video content scoring from human sentiment, for recommendations and segment highlighting
Improved low-latency live-streaming and P2P broadcast
Integrated and benchmarked client-side face/object detection, body tracking, and region-of-interest selection

Computer Vision Cross-modal AI Video ML Recommendation Systems

Sep 2018 – Jan 2022 · Tveon (3 yrs 5 mo)

Senior Researcher

Tveon

Led a team of video researchers building custom encoding tools and scalable compute infrastructure
Team spanned video engineers, developers, psychologists, neuroscientists, and data scientists

Python / OpenCV TensorFlow AWS Docker / Kubernetes

Nov 2012 – Sep 2018 · Tveon (5 yrs 11 mo)

Senior Cloud Architect

Tveon

Designed and led development of CMS and automated transcoding for live-streaming and critical infrastructure monitoring
Mobile app with location-aware auto-selection of live IP camera feeds for on-site security
Built custom encoding and CMS for multi-channel entertainment content with in-app micro-gaming
Established a talent pipeline from the local university's Math/CS program

Apr 2016 – Sep 2018

Director of Technology

Prosmart / Rosterbot / Sportgo

Architected the product as it expanded into four business verticals; integrated acquisition of Metabridge Top 15 startup Rosterbot
NLP-driven analysis of internal communications to measure community health
Co-developed a computer vision tool with UBCO partners to detect brand presence in user-uploaded images
ProSmart became the first company from the regional accelerator listed on the TSX

NLP Computer Vision AWS Rekognition

Jul 2018 – Oct 2018

Technical Consultant

Innovate BC

Consulted on the AI Justice Challenge with BC Ministry of Justice
Defined requirements and training data design for multi-modal AI applications (speech-to-text, translation, AI-guided retrieval)

Jan 2018 – Apr 2018

Lecturer — Digital Citizenship (COSC 101)

University of British Columbia

Taught 150–200 first-year students on digital platforms, online safety, cloud computing, and ML in social media

Jan 2011 – Dec 2021

Co-Organizer

Digital Okanagan / Startup Coffee / Data Science Meetup

Co-organized tech community events across Kelowna for 10+ years
Bridged UBCO faculty and local industry, with a current focus on AI advances

Jun 2011 – Oct 2012

Senior System Architect

Worldplay

Built a full-stack system to simulate and analyze 100k+ simultaneous video streaming sessions
Models for network issue simulation, user satisfaction tracking, and encoding quality feedback

Jan 2009 – Aug 2010

Postdoctoral Research Fellow

University of British Columbia

Research across Mathematics, Statistics, and Computing Science
Visualization of iterative projection method convergence; optimization on non-convex functions
Applied global optimization to open problems in statistical modelling

Optimization Non-convex Functions Statistical Modelling

2000 – 2002

Research Assistant

Packeteer Canada

Developed a (now-patented) method for re-encoding images to minimize visual artifacts relative to target filesize
Led human-subject experiments evaluating automated image encoding quality

Background

PhD, Computer Science

Dalhousie University

2004 – 2008

PhD Candidate, Mathematics

Simon Fraser University

2002 – 2004

MSc, Mathematics

2000 – 2002

BA, Mathematics

University of British Columbia

1995 – 2000

Mar 14, 2026

A Pi Day Memorial to Dr. Pi

A tribute to Jonathan Borwein ("Dr. Pi"), reflecting on Pi Day and working in his mathematics lab on experimental approaches to research.

Building AI that
actually ships.

The short version