Founding Machine Learning Engineer

Position Overview

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.

What You'll Do

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.

What We're Looking For

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

This role probably isn't for you if you're looking to join an established ML team where you can learn from senior engineers, if you prefer specializing deeply in one area rather than being a generalist, or if you need a remote or hybrid setup.

Interview Process

• Round 0: Phone ScreenQuick conversation with the hiring manager about the role, your background, and what you're looking for.

• Round 1: Technical Interview(2 hours, in-office) Meet with 2-3 engineering leaders for an algorithm/SQL problem, an ML system design case study, and a walkthrough of your past work.

• Round 2: Paid Work Trial(2 days, in-office) Two days working alongside the team in our actual codebase on real problems. You'll be paid a competitive daily rate. This lets us see how you work, and lets you see our actual culture, team dynamics, and whether you'd enjoy it here.

• Round 3: CEO Chat Usually happens during the work trial. Non-technical conversation about culture and working style.

Timeline: Typically 1-4 weeks from application to offer. We move quickly and work with your schedule.

Compensation & Benefits

Compensation:

- Competitive base salary

- ISO equity grant

- Performance-based bonuses for high-impact work

Benefits:

- Health, dental, and vision insurance with HSA contributions

- Flexible PTO and parental leave

- On-site gym with pickleball and basketball

- Monthly allowance for purchases from e-commerce stores

- $100/month babysitting reimbursement

This role is 100% in-office in Draper, Utah. Relocation assistance available for the right candidate.