Founding Machine Learning Engineer

Redo•Draper, UT

3d•Onsite

About The Position

Redo has billions of e-commerce data points from 3,000+ merchants, and we're barely scratching the surface of what's possible with it. As our founding ML engineer, you'll be the one to unlock that value. This is an IC role. You'll write code every day, ship models to production, and make the infrastructure decisions from the ground up. Our ideal candidate is self-driven, comfortable with ambiguity, and energized by building something new. About Redo Redo is a post-purchase commerce platform that consolidates returns, order management, marketing, checkout optimization, and customer support into a single system for e-commerce brands. We serve 3000+ merchants and help them turn post-purchase operations into a revenue driver. We're a Series A company with just under 200 employees, profitable and growing. Based in Draper, Utah. We have early ML models that are already showing promise, but we don't have anyone in house who really knows what they're doing with them yet. That's where you come in. You'll own model development from research to production, make the infrastructure and tooling decisions, and set the technical direction for data science at Redo. Some of the problems you'll work on: Product recommendations - Upsell recommendations across millions of transactions, using purchase and return history, cart data, and browsing behavior to surface the right offer at the right time Checkout intent prediction - Predict mid-session purchase likelihood so we can trigger targeted promotions before at-risk shoppers bounce Inventory forecasting - Predict restock timing and quantities across thousands of SKUs, accounting for seasonality and trends Plus identifying and building new high-value ML applications across the platform You'll also build out our ML infrastructure (we have a scrappy Metaflow/Sagemaker setup you can build on or replace), work closely with product and data teams to find new opportunities, and lead the function as it grows.

Requirements

Someone who has shipped models to production, debugged why they degraded, and owned the full lifecycle. We care more about what you've built than credentials.
Strong Python and modern ML frameworks (PyTorch, scikit-learn, etc.)
Experience building ML infrastructure (training pipelines, deployment, monitoring)
Data engineering chops: pipelines, complex SQL, messy data quality issues
Bias toward action. You'd rather ship and iterate than plan indefinitely
Business mindset. You think in terms of revenue impact, not just model metrics
Comfortable being the only ML person in the room for a while

Responsibilities

Own model development from research to production
Make the infrastructure and tooling decisions
Set the technical direction for data science at Redo
Product recommendations - Upsell recommendations across millions of transactions, using purchase and return history, cart data, and browsing behavior to surface the right offer at the right time
Checkout intent prediction - Predict mid-session purchase likelihood so we can trigger targeted promotions before at-risk shoppers bounce
Inventory forecasting - Predict restock timing and quantities across thousands of SKUs, accounting for seasonality and trends
Identifying and building new high-value ML applications across the platform
Build out our ML infrastructure
Work closely with product and data teams to find new opportunities
Lead the function as it grows