ML Engineering · Logistics & Operations AI
ML engineering across FedEx and ThredUp. I help logistics operators and 3PLs turn messy operational data into reliable ML systems — delivery forecasting, loss prevention, computer vision for warehouses.
in Let's connect!Package fraud alerting system — built an ML loss prevention platform that surfaced stolen packages and saved a flagship enterprise contract from churn.
FedEx · 2022–2024
Pose estimation for garment measurement — CV model eliminated a manual QA workflow, reducing labor costs at scale in a high-throughput ops environment.
ThredUp · 2024–Present
Estimated delivery date forecasting — improved production EDD prediction on FedEx.com, directly reducing customer service load.
FedEx · 2022–2024
About
I grew up in Arizona, finished a 4-year degree in Business Data Analytics at ASU in two years at 19, then went straight into industry. At State Farm I ran A/B testing on telematics products. At FedEx I spent three years building ML systems at carrier scale — capex optimization, estimated delivery date forecasting, and a fraud detection platform that recovered $300M in revenue and triggered 100+ internal terminations for theft.
After completing my MS in Computer Science from Georgia Tech during COVID, I joined ThredUp as a Senior ML Engineer, where I own the full lifecycle of computer vision models in operations — from ideation through production — and manage the 2025 and 2026 ML intern program.
Outside of work, I mentor ML and data science career changers, and consult for early-stage companies on analytics engineering and ML development. I'm selectively available for consulting engagements with 3PLs and logistics operators who are serious about building durable AI systems.
What I do
EDD forecasting models that reduce customer service load and improve on-time perception — built from real carrier-side experience at FedEx scale.
ML systems that detect stolen and missing packages before they become contract losses. I've done this at $300M enterprise scale.
CV models for package classification, damage detection, proof-of-delivery auditing, and measurement automation in high-throughput environments.
For teams that know they need ML but aren't sure where to start — I scope the problem, identify the ROI, and build toward it.
Career
Sr. Machine Learning Engineer
Jun 2024–Present · Scottsdale, AZ
End-to-end ownership of AI models in operations — from ideation through production deployment. Built pose estimation and landmarking models for garment measurement automation. Manage the 2025 and 2026 ML intern program.
$1M+ annual labor cost reduction via computer vision
Data Scientist II
Apr 2022–Jun 2024 · Remote
Built the fraud alerting platform that became FedEx's primary internal tool for identifying stolen packages and at-risk enterprise accounts. Also owned EDD forecasting improvements and proof-of-delivery image auditing.
$300M+ revenue saved
Operations Research Engineer
Jan 2021–Apr 2022 · Remote
Built the Python tooling and analysis that powered a $1.2B capex optimization research initiative. All $300M in facility upgrade proposals approved by executive stakeholders.
$1.2B+ capex initiative supported
Process Engineer
Jun 2019–Dec 2020 · Tempe, AZ
Led A/B testing and statistical inference for new telematics products. Also led RPA process automation projects.
5% crash detection lift
Education
MS, Computer Science
2020–2022
Specialization: Machine Learning. Completed remotely during COVID.
BS, Business Data Analytics
2017–2019
Completed a 4-year program in 2 years at age 19. W.P. Carey School of Business.
I take a small number of consulting engagements each year with 3PLs, fulfillment operators, and logistics tech teams. If you're not sure whether your problem fits, reach out — I'll tell you honestly.
Writing
Notes on ML systems, logistics operations, and building for production.