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Koah

AI-driven ad network for monetization

Applied Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$200k - $300k /yrHybrid

About the Job

Requirements

  • An advanced degree in Physics, Computer Science, Mathematics, Statistics, Engineering, or a related field.
  • Strong mathematical and statistical modeling skills.

Responsibilities

  • Identify and own challenging problems, form testable hypotheses, and conduct impactful research to drive business impact.
  • Communicate conclusions to technical and non-technical audiences.
  • Design efficient algorithms for real-time bidding systems, building upon current pricing literature.
  • Create and productionize regression models to predict end conversions using demographic, audience, and semantic data.
  • Apply privacy-preserving clustering methods to categorize conversational data and improve advertiser outreach.
  • Analyze data to identify improvements to the core ad matching system while balancing publisher and advertiser outcomes.

Desired Qualifications

  • Continuously learn, make an impact, and question the status quo.

About the Company

Koah

AI-driven ad network for monetization

KOAH Labs runs an AI-driven ad network designed to work inside AI applications for both advertisers and publishers. For advertisers, it uses precise targeting to match ads with user intent, improving efficiency and lowering customer acquisition costs. For publishers, it provides an ad-supported free tier to grow revenue and audience, supporting sustainable growth. The platform allows easy testing using existing text creatives without requiring channel optimization, making cost-effective testing straightforward. What makes KOAH Labs different is its integration into AI apps, emphasis on high-relevance placements and user experience, and a simple testing approach that reduces setup complexity. The company's goal is to help advertisers reach high-intent users with relevant ads while enabling publishers to monetize AI-enabled experiences in a scalable, cost-efficient way.

Company size
11-50
Company stage
Series A
Total funding
$25.5M
Headquarters
San Francisco, CA
Founded
2024

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