Applied Ai / Ml Scientist - Ads Bidding

Faire

San Francisco, CA, United States
Base: $165,500 to $227,500 py; bonus/equity: eligi...
On-site
Ml models for auction optimization
Bid shading and multipliers
Budget allocation and pacing
Own the end-to-end development of ML models across the ads bidding stack—from problem framing, solution design, modeling, and implementation to deployment, experimentation, and impact measurement

Job Summary

  • Own the end-to-end development of ML models across the ads bidding stack—from problem framing, solution design, modeling, and implementation to deployment, experimentation, and impact measurement.
  • Define and improve bidding and pacing strategies that balance advertiser performance, marketplace health, and platform economics (e.g., spend smoothing, delivery guarantees, seasonal demand, and inventory constraints).
  • As an early member of the Ads Data team, help define its roadmap and technical culture, leveraging deep product intuition to shape what ads at Faire *should* be—not just how they’re built.

Matching Summary

Own the end-to-end development of ML models across the ads bidding stack—from problem framing, solution design, modeling, and implementation to deployment, experimentation, and impact measurement.

Salary

Base: $165,500 to $227,500 per year; Bonus/Equity: eligible for equity; Benefits: eligible for benefits

Skills & Requirements

Must-have

  • ML models for auction optimization
  • Bid shading and multipliers
  • Budget allocation and pacing
  • Advertiser ROI/ROAS optimization
  • Marketplace optimization best practices
  • Experimentation best practices

Nice-to-have

  • Deep product intuition
  • Fast-paced collaborative environment
  • Shipping ML at top tech companies

Key Requirements

  • 2+ years industry experience
  • Full ML lifecycle ownership
  • Strong programming skills
  • Experience with SQL
  • Ability to lead model development

Work Rights

Not specified

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