Applied AI/ML Scientist, Intern

Faire is an online wholesale marketplace that connects independent brands with local retailers. We use machine learning and data insights to help those small businesses compete against giants like Amazon and big box stores.

Our Applied AI/ML Science team builds and maintains the models that power the marketplace. That work includes the shipping and delivery estimates retailers rely on as they shop and check out: what it will cost to ship and when it will arrive, before the order has been packed. Within Applied Science, our Shipping and Fulfillment team builds the models behind those estimates, including models that learn to understand products from images and text. Better predictions give retailers confidence in what they're buying and, in turn, help brands sell more on Faire.

We're looking for people who thrive on tricky problems: who dig into rich data, come up with ideas that work, and take the best of them all the way to production.

You'll own a focused project in one of these areas:

• →Predicting how an order will be packed: Before an order ships, we have to anticipate how it will be packed. You'll build models that learn from what each item is and how items combine in a cart.
• →Recommending better ways to pack: How an order is packed shapes what it costs to ship. You'll develop models that understand items from images and text and learn from historical packing outcomes to recommend packing that reduces shipping cost and improves efficiency.
• →Understanding products from a catalog: Listings often lack reliable weight, size and shape. You'll train multimodal deep learning models that infer these physical characteristics from images, text and other catalog signals.

Whichever project you take on, you will:

• →Survey the literature and existing approaches to identify promising ideas
• →Prototype and train models offline, benchmarking against our current methods
• →Build out the strongest approach into a working implementation
• →Work with Applied Scientists and ML Engineers to test it against live traffic
• →Present findings and recommendations to the team

• Currently enrolled in or recently graduated from a Master's or PhD program in Computer Science, Machine Learning, Statistics, Electrical Engineering, or a related technical field
• Hands-on experience building deep learning models (e.g., PyTorch), ideally with images, text, or both, including fine-tuning pre-trained models or working with embeddings
• Familiarity with gradient-boosted trees and other tabular ML methods
• Strong Python and SQL
• Ability to read research papers and turn promising ideas into working code
• Solid grounding in statistics and model evaluation, including benchmarking against strong baselines and estimating uncertainty
• Comfort working with noisy or incomplete real-world data
• A genuine enthusiasm for tackling ambiguous problems and learning new tools and techniques

This paid Winter 2027 internship runs for 12 to 14 weeks, beginning in January 2027, with flexible start dates available for qualified candidates. Extensions may be offered based on project needs and mutual agreement.

San Francisco: the pay rate for this role is $75 USD per hour.

Actual hourly pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

#LI-DNI

• 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)

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)