ML Engineer, Whop Ads

About the Role

The ads team owns the product surfaces that drive growth for businesses on Whop. As an ML engineer on ads, you will work as the strategist behind Whop's autonomous ad operator - the system that decides what every business on Whop should test, how to allocate budget, and what to do with the results - shipping it into a live loop already wired into ad platforms and creative generation. Smarter decisions mean better ads, lower CAC, and more revenue for every business on Whop.

About Whop

Whop is a financial technology company on a mission to provide the world with sustainable income. Our vision is to create the world’s largest internet market, where people can create, connect, and transact all from a single platform. Whop enables individuals and businesses to accept payments, launch ventures, and engage with others across the network.

Today, Whop facilitates over $3 billion in annual payouts to people in 144 countries. Growth continues to accelerate, with gross transaction volume increasing roughly 25% month over month.

Whop has raised hundreds of millions from institutional investors like Insight, Bain Capital Ventures, A*, and Peter Thiel — including a recent strategic investment from Tether, the largest stablecoin company in the world.

Our current team is made up of young, passionate entrepreneurs who grew up on the internet — over 75% built a business before joining Whop, including 53 former founders and 30 who scaled past $1M in revenue. Product leadership includes backgrounds from Meta and Robinhood.

For more information, visit whop.com.

What you'll do

• Work on the closed-loop ads agent end to end — classification, strategy, creative selection, budget allocation, measurement, iteration
• Pick the right tool for each sub-problem
• Turn campaign outcomes across every business on Whop into training signal that compounds
• Build the evals that prove the agent is improving

What you need

• Minimum of 5 years experience in software development and or ML engineering roles
• Comfort making real decisions with noisy, delayed, expensive reward signals — you've worked on a problem where the feedback loop costs real money or real users
• Ability to ship fast, reliable software in a startup with imperfect information
• Excellent communication — you'll be the person translating "the agent did X because Y" to non-ML teammates and customers

Nice to have

• Startup experience or experience as a technical founder
• You've shipped an agentic system with real tool use and a real feedback loop in production — not a demo
• Comfortable thinking about attribution, incrementality, and the difference between a metric moving and a metric mattering
• Experience with offline RL, RLHF, or fine-tuning LLMs on production outcome data

Benefits overview

• ✅ Base salary of $250K+ a competitive equity package + opportunity for ownership in product's success 
• ❤️ Unlimited PTO, with full health, vision, dental coverage
• 🍕 Lunch & dinner paid for Monday through Friday
• 🏋️‍♀️ Free Equinox membership
• 💻 Latest MacBook Pro & tech accessories