Applied AI / ML Scientist - Ads Bidding

About the role

The Ads Data team is building the next generation of advertising products for the wholesale industry. As a key member of this team, you’ll shape the future of our ads marketplace and auction system at Faire—spanning auction design, bidding strategy, pacing, pricing, and budget optimization.

This is a rare opportunity to be an early contributor to a fast-growing team in an incredibly strategic area of the business. Ads is a major company priority and you'll have a massive impact in shaping the platform that connects independent retailers and brands.

Qualifications

• 2+ years of industry 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.
• Strong programming skills.
• 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.
• The ability to quickly implement state of the art algorithms from an academic paper.

Pay, Benefits & Schedule

Salary Range
San Francisco: the pay range for this role is $165,500 to $227,500 per year.
This role will also be eligible for equity and benefits.

Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location.

Hybrid
Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday).

Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year.

Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting.