Native ads powered by real-time intent matching — not borrowed from the last era. The monetization layer for AI apps. Backed by South Park Commons.
About the role
You have an advanced degree in Physics, Computer Science, Mathematics, Statistics, Engineering, or a related field You enjoy identifying and owning challenging problems, forming testable hypotheses, and conducting impactful research to drive significant business impact
What they're looking for
- You have an advanced degree in Physics, Computer Science, Mathematics, Statistics, Engineering, or a related field
- You enjoy identifying and owning challenging problems, forming testable hypotheses, and conducting impactful research to drive significant business impact
- You have a relentless focus on continuous learning and making an impact with an ability to question the status quo
- You have strong mathematical and statistical modeling skills
- You enjoy communicating conclusions to both technical and non-technical audiences alike
More about this role
Koah Labs is building the ad network to power the next generation of AI-native products. Our mission is to help publishers monetize and help advertisers reach the right audience — without compromising speed, UX, or privacy.
We’re a small, tight-knit team in San Francisco with backgrounds at X, Apple, Meta, and early-stage startups. We’ve raised from top investors and are growing fast with real traction on both the publisher and advertiser sides.
Working at Koah means joining at the ground floor: you’ll ship code that shapes the company and the ecosystem we’re building. We move quickly, operate with high trust, and care deeply about craft.
Infra : Terraform, AWS, LGTM (Loki, Grafana, Tempo, Mimir), Tailscale, Cloudflare
Data : PostgreSQL, ClickHouse, Redis, Kafka, Python
Core Application : Ruby on Rails, React, TypeScript
SDKs : Flutter, React Native, Android, iOS
Design efficient algorithms for real-time bidding systems, building upon the current pricing literature
Create and productionize regression models to predict end conversions based on demographic, audience, and semantic data
Apply privacy-preserving clustering methods to categorize conversational data to improve advertiser...
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