Applied Scientist

About this role

Who We Are

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.

Our Stack

- 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

Example Projects

- 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 outreach

- Analyze and pore over data to find alpha that can improve the core ad matching system balancing publisher and advertiser outcomes

You might be a fit if

- 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

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