Applied AI / ML Scientist - Ads Bidding

Responsibilities

• 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.
• Build best-in-class models and algorithms for auction optimization, bid shading and bid multipliers, budget allocation, pacing, and advertiser ROI/ROAS optimization—drawing from marketplace optimization and experimentation best practices.
• 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).

Requirements

• At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe.
• Work in a fast-paced, collaborative environment with team members who’ve shipped ML at top tech companies (e.g. Uber, Airbnb, Meta, Amazon, Pinterest).
• experience using machine learning to solve real-world problems, ideally in Ads, Marketplace Optimization, Pricing, Auctions, or a related large-scale production domain.
• Demonstrated ownership of the full ML lifecycle: from scoping and design through training, deployment, A/B testing, and iteration.
• Experience with relational databases and SQL.
• The ability to contribute to team strategy and to lead model development without supervision.
• Strong communication skills and the ability to work with others in a closely collaborative team environment. Great to Haves
• Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
• Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day.

Experience

• 2+ years of industry

Benefits