Job Description

About Faire

Faire is an online wholesale marketplace built on the belief that the future is local — independent retailers around the globe are doing more revenue than Walmart and Amazon combined, but individually, they are small compared to these massive entities. 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 that small businesses everywhere can compete with these big box and e-commerce giants.

By supporting the growth of independent businesses, Faire is driving positive economic impact in local communities, globally. 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:

Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. Our highly skilled team of data scientists and machine learning engineers specializes in developing algorithmic solutions related to discovery, ranking, search, recommendations, ads, logistics, underwriting, and more. Our ultimate goal is to empower local retail businesses with the tools they need to succeed.

As a member of the Discovery Personalization team, you’ll be responsible for: 

• Personalization : Personalizing recommendations across surfaces of homepage, category page, brand page, and carousel recommendations, through retrieval embeddings models, near-real-time / streaming signals, Deep Learning or LLM-based ranking/recommendation models, explore-exploit, and diversification

Our team already includes experienced Data Scientists and Machine Learning Engineers from Uber, Airbnb, Square, Meta, LinkedIn and Pinterest. We're a lean, talented team with high opportunity for direct product impact and ownership. 

You’re excited about this role because… 

• You’ll be able to work on cutting-edge personalization and recommendation problems by combining a wide variety of data about our retailers, brands, and products


• You want to use machine learning to help local retailers and independent brands succeed 


• You want to be a foundational team member of a fast-growing company


• You like to solve challenging problems related to a two-sided marketplace 

Qualifications 

• 1-3 years of relevant industry or research experience applying ML to real-world problems


• Familiarity or experience with personalization systems or recommendation algorithms


• Proficiency in Machine Learning / Deep Learning modeling and programming 


• An excitement and willingness to learn new tools and techniques 


• Strong communication skills and the ability to work with others in a closely collaborative team environment 

Great to Haves:

• Master’s or PhD in Computer Science, Statistics, or related STEM fields 


• Experience implementing state-of-the-art ML algorithms from an academic paper


• Exposure to graph neural networks and/or language models

Salary Range

California & New York: the pay range for this role is $162,500 to $223,500 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.

Effective January 2025, Faire employees will be expected to go into the office 2 days per week on Tuesdays and Thursdays. 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

• We are entrepreneurs: Faire is being built for entrepreneurs, by entrepreneurs. We believe entrepreneurship is a calling and our mission is to empower entrepreneurs to chase their dreams. Every member of our team is taking part in the founding process.


• We are using technology and data to level the playing field: We are leveraging the power of product innovation and machine learning to connect brands and boutiques from all over the world, building a growing community of more than 350,000 small business owners.


• We build products our customers love: Everything we do is ultimately in the service of helping our customers grow their business because our goal is to grow the pie - not steal a piece from it. Running a small business is hard work, but using Faire makes it easy.


• We are curious and resourceful: Inquisitive by default, we explore every possibility, test every assumption, and develop creative solutions to the challenges at hand. We lead with curiosity and data in our decision making, and reason from a first principles mentality.

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 (

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