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RZR

Cross-channel DSP for growth marketing

Head of Machine Learning

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USANo salary listedIn-person

About the Job

Requirements

  • At least 7 years of experience focused on building production machine learning systems.
  • Experience taking machine learning models from research or prototype to production at scale.
  • Strong programming background in Python and at least one systems language: C++, Java, Rust, or Go.
  • Experience working with large-scale data pipelines and training infrastructure.
  • Ability to operate in an early-stage environment as both architect and implementer.
  • Strong product intuition and ability to prioritize machine learning work based on business impact.
  • Experience scaling machine learning teams.
  • Fluent Mandarin is required.

Responsibilities

  • Design and build the next generation production machine learning system, including training pipelines, feature pipelines, and real-time inference services.
  • Work directly in the codebase to prototype models, evaluate approaches, and ship production systems.
  • Build and lead the machine learning team, including hiring, mentoring, and establishing engineering culture.
  • Partner with engineering to design infrastructure capable of serving millions of low-latency predictions.
  • Identify high-impact machine learning opportunities across bidding, ranking, pacing, fraud detection, and optimization.
  • Establish best practices around experimentation, model evaluation, monitoring, and continuous improvement.
  • Translate business and product goals into measurable machine learning improvements.

Desired Qualifications

  • Experience in advertising technology and real-time systems.
  • Experience operating machine learning infrastructure in on-premises environments using open-source tools including Spark, ClickHouse, AeroSpike, and Prefect.

About the Company

RZR

Cross-channel DSP for growth marketing

RZR is a growth marketing intelligence platform that unifies and optimizes advertising campaigns across mobile, retargeting, and Connected TV. Its DSP uses a proprietary neural architecture to analyze billions of signals in real time and predict a user’s lifetime value before bidding, guiding campaigns toward higher-value outcomes like ROAS and long-term retention. The platform emphasizes cross-channel integration and a single connected performance system, powered by global data centers and ML models to scale for brands in gaming, retail, and entertainment. The goal is to help brands increase marketing effectiveness across channels through value-based bidding and attribution.

Company size
51-200
Company stage
Acquired
Total funding
$1.7M
Headquarters
United States
Founded
2010

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