Joe Waugh

Joe Waugh

I build machine learning that makes operations measurable, and help grow the teams that keep it running.

I'm a senior machine learning engineer at ThredUp in Scottsdale, where I build computer vision and ML for our distribution centers, from first idea to production. This year I led the Algorithms team for a quarter, wrote the team's AI roadmap for 2027, and started building the shared infrastructure that lets teams run AI agents safely.

Before that I spent three years at FedEx. I started in operations research, building the tooling behind a $1.2B capital plan, then moved into data science, where I built the fraud alerting platform that kept a $300M customer from leaving. I started my career at State Farm, running experiments on telematics products.

I finished my undergraduate degree in business data analytics at Arizona State in two years, at 19, and earned an MS in computer science from Georgia Tech while working full time.

Outside my day job, I mentor students through Georgia Tech and Arizona State, serve as a peer mentor on AI, and take on a little advising.

Selected results

At ThredUp

$1.4M
a year in labor saved by automating garment measurement with pose-estimation models.
98%
of pant measurements now automated, up from about 80%, which accounts for about $400K of that.
1.9%
measurement error on flat-lay pants, down from 16.6%. Skirts went from 22.3% to 1.3%.
49%
of item intake fully automated, up from about 42%, after shipping an ML sizing model.
91.3%
on-time delivery-date promises across about 330,000 boxes, from a shipment forecast built for Supply Chain.
0.4%
of generated product images rejected for wrong orientation, down from 5.1%.
23 ms
model latency after moving serving from SageMaker to Kubernetes, down from 38 ms.

At FedEx

$300M
customer relationship saved by a fraud alerting platform that found where packages were disappearing. Read the story.
$1.2B
capex initiative built on my tooling. All $300M in proposed facility upgrades were approved.
$3M
in projected revenue from an image model that catches packages owed a surcharge.
$2M
a year saved by a model that audits proof-of-delivery photos. Read the story.
5%
more accurate delivery dates on FedEx.com.

Career

  • Work
  • Study
  • Mentoring and hiring
Work
Study
Mentoring
Interns and hiring

Drawn to scale. Select a bar to jump to that role. Swipe the chart to see earlier years.

  • ThredUp, Senior Machine Learning Engineer. 2024 to now.
  • FedEx Ground, Data Scientist II. 2022 to 2024.
  • FedEx Ground, Operations Research Engineer. 2021 to 2022.
  • State Farm, Process Engineer. 2019 to 2020.
  • Georgia Tech, MS in Computer Science (machine learning). 2020 to 2022.
  • Arizona State, BS in Business Data Analytics. 2017 to 2019.

Full resume (PDF)

Mentoring and teaching

  • Mentor to students at Georgia Tech and Arizona State since 2022, and a peer mentor on AI.
  • Run ThredUp's ML intern program for 2025 and 2026. Hired three interns and a full-time engineer.
  • Helped 8+ career changers build the skills to land data science roles.
  • Taught a computer vision workshop for 15+ data scientists at FedEx.

Talks

  • What is a machine learning engineer, and how to break into the field, Estrella Mountain Community College, Work Ready WednesdayApril 2026
  • Automating ML experiments with autoresearch, ThredUp AI engineering productivity seriesApril 2026
  • Running LLMs locally, ThredUp AI engineering productivity seriesJune 2026
  • A generative image explorer for product photos, ThredUp AI ShowcaseJuly 2026
  • Flaw detection with computer vision, ThredUp operations updateAugust 2026
  • Flat-lay measurement R&D, Distribution center operations offsiteOctober 2026

Writing

All writing or follow by RSS

Advising

I take on a small number of advising engagements with operations and health tech teams that want ML they can rely on: loss prevention, delivery estimates, warehouse computer vision, or working out where to start. Past work includes analytics engineering and ML development for Float Health, an early-stage health care company, in 2024.

Get in touch

I like hearing about hard operations problems, leadership roles, and people getting started in ML. The fastest way to reach me is a message on LinkedIn.

Send a message here

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