Applied Scientist
Listed on 2026-07-25
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IT/Tech
Data Scientist, AI Engineer (Applied/Software), Data Analyst, Machine Learning/ ML Engineer
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 StackInfra
:
Terraform, AWS, LGTM (Loki, Grafana, Tempo, Mimir), Tailscale, CloudflareData
:
PostgreSQL, Click House, Redis, Kafka, PythonCore Application
:
Ruby on Rails, React, Type ScriptSDKs
:
Flutter, React Native, Android, iOS
Example Projects
Design efficient algorithms for real-time bidding systems, building upon the current pricing literature
Create and product ionize 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 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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