Founding Machine Learning Engineer

About Booko:

Booko is dynamically pricing anything you can book. Airlines and hotels have priced by demand for decades. Gyms, studios, clinics and all time-slot based services are a massive slice of the economy that still charge one flat price and watch open slots perish. We fix that.

We integrate into the booking systems these businesses already run on forecast demand class by class and slot by slot, and move price and incentives in real time to fill inventory. We are live in production with some of the largest national fitness brands, boutique studios, clinics, and chains.

We are a small team that ships fast and stays unusually close to the work. Everyone here talks to customers, owns whole surfaces end to end, and cares about the outcome, not the ticket. We're hiring our founding engineering team and would love for you to be a part of it!

About the role

You'll own how Booko thinks. We are building a superintelligent demand- forecasting and pricing brain that forecasts demand better than anyone in the world and knows exactly how to price against it. You own the models that decide what every class, appointment, and slot should cost. You will be improving our ML systems and our customer-specific agents in production today.

• Owning the demand-forecasting models end to end: predicting how full any bookable slot will be by fusing full historical data, live signals, and market conditions into one engine

• Modeling how demand responds to price and incentives, and turning that into real-time, revenue-optimal pricing decisions

• Building the always-on agents that act on the engine: autonomous systems that monitor, decide, and take action across customer systems in real time

• Pushing the frontier: new signals, richer representations, and models that generalize across very different verticals from a single platform

• Measuring true causal impact through live experiments, and keeping the models sharp and trustworthy in production at scale

You'll be a good fit if

• You're a strong ML engineer who can take models from research to production, fluent in Python and the modern ML stack
• You've built agents or autonomous systems that take real actions in production, not just demos
• You think in evals, metrics, and causality, and care what they mean in the real world, not just on a holdout set
• You want to own the full loop, from data and modeling to the revenue it moves, in person in SF or NYC