Applied AI / ML Scientist - Ads Bidding

About Faire

Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive.

We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.

About this 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. Our in-house stack gives us unique end-to-end ownership, and our first-party conversion data allows us to train highly effective models and optimize for real, business-critical outcomes on behalf of our brands.

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. You’ll work closely with engineers, product managers, and designers to launch and iterate on systems that are not just technically sophisticated, but also directly drive improvements to the bottom line for both brands and Faire.

What You'll Do

• 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).
• 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.
• 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).

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
• Ability to quickly implement state of the art algorithms from an academic paper

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. The base pay range provided is subject to change and may be modified in the future.

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. 

Why you’ll love working at Faire

• Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.
• 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.
• Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours.
• Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.
• Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.

Faire was founded in 2017 by a team of early product and engineering leads from Square. We’re backed by some of the top investors in retail and tech including: Y Combinator, Lightspeed Venture Partners, Forerunner Ventures, Khosla Ventures, Sequoia Capital, Founders Fund, and DST Global. We have headquarters in San Francisco and Kitchener-Waterloo, and a global employee presence across offices in Toronto, London, and New York. To learn more about Faire and our customers, you can read more on our blog.

Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression.

Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs.  To request reasonable accommodation, please fill out our Accommodation Request Form (https://bit.ly/faire-form)

Privacy

For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire’s Privacy Notice (https://www.faire.com/privacy)