---
title: 'Applied AI/ML Scientist, Intern at Faire'
canonical: 'https://feeny.ai/job/applied-ai-ml-scientist-intern-faire-san-francisco-wvyy8ewrrw0p'
type: 'job'
last_seen: '2026-10-15'
---

# Applied AI/ML Scientist, Intern at Faire

- **Company:** Faire
- **Location:** San Francisco, CA
- **Posted:** 2026-10-06
- **Last confirmed live:** 2026-10-15
- **Apply:** https://boards.greenhouse.io/faire/jobs/8870975002?gh_jid=8870975002

## Job description

## 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

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.

## What you will be doing

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

What it takes

- 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

Internship Details

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.

Pay rate

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

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](https://blog.faire.com/).

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://docs.google.com/forms/d/e/1FAIpQLSczpI9me7nYKhunSC6AlagHKv75LHqfi-Qi2TP_3dpin0Uc9Q/viewform) (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 https://www.faire.com/privacy

## About Faire

## Company Overview
- **One-liner**: Faire is an online wholesale marketplace that connects independent retailers with brands to streamline the buying and selling process, empowering local businesses.
- **Entity Type**: Private (Series E, $1.7B total funding)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2017
- **Founders**: Max Rhodes (CEO), Daniele Perito (CTO), Marcelo Cortes (COO), and Rekha Srivatsan

## Core Business
- **Primary industry/industries**: Wholesale Marketplace / E-commerce / Retail Technology
- **Target customers**: B2B – primarily independent retailers (boutiques, grocery stores, gift shops) and brands/manufacturers.
- **Mission or purpose statement**: "To empower brands and retailers to strengthen the unique character of local communities."

## Products & Services
- **[Faire Marketplace]**: The core platform is a two-sided wholesale marketplace. Retailers can discover and buy products from thousands of brands with low minimums, net-60 payment terms (60 days to pay, interest-free), and free returns on first orders.
- **[Faire Payments & Invoicing]**: Integrated financial services allowing retailers to buy now and pay invoices 60 days later with zero fees.
- **[Faire for Brands]**: A suite of tools for brands to manage their wholesale operations, get discovered by retailers, and manage orders and payments.

## Market Standing
- **Valuation/Market Cap**: $12.59 billion (as of Series E in 2021, per multiple reports and LinkedIn). Note: This is a private valuation from 2021; current valuation may differ.
- **Key Metric**: Annual Revenue of $235M (estimated, per LinkedIn) and Total Funding of $1.7B.
- **Notable Investors/Partners**: Sequoia Capital (led Series E), Khosla Ventures (led Series A), Forerunner Ventures, DST Global, Lightspeed Venture Partners, Founders Fund, Y Combinator.
- **Growth Signals**: 
    - Headcount of 927 employees (+8.6% YoY growth).
    - Serving retailers in 70,000+ cities and featuring 100,000+ brands.
    - Named to Forbes "Top Startups of 2025" list.
    - Received Fast Company "Most Innovative Companies" award.
    - Active job postings up +147.4% YoY, signaling strong hiring momentum.

## Competitive Advantages
- **Network Effects**: A powerful two-sided marketplace that becomes more valuable as more retailers and brands join.
- **Financial Moat**: Offering net-60 payment terms is a major differentiator for cash-strapped small retailers, creating stickiness.
- **Data & AI**: Uses AI/ML to power search, recommendations, and pricing, helping retailers discover the right products and brands optimize their offerings.
- **Scale & Brand**: As the leading platform in its space, it has a significant head start over potential competitors.

## Strategic Focus
- **International Expansion**: Offices in Canada, UK, Brazil, Netherlands, and India, with plans to grow.
- **Product Development**: Heavy investment in AI/ML (hiring Applied AI/ML Scientists), product management, and design to improve the platform experience.
- **Deepening the Moat**: Focus on financial services (payments/invoicing) and data insights to become an indispensable operating system for independent retailers.

## Why Work Here
- **Culture**: The company emphasizes a "high-urgency," "relentlessly resourceful," and "low-ego" culture. Core values include "One Faire" (collaboration), "Make it happen (fast)," "Raise the bar," "Seek the truth," and "Serve our community."
- **Remote/Hybrid/Office Policy**: Hybrid model with thoughtfully designed offices in San Francisco (HQ), New York, Toronto, Waterloo, London, and São Paulo. Monthly stipends for home connectivity needs.
- **Notable Perks**:
    - Comprehensive healthcare (Health, Dental, Vision, Disability).
    - Generous parental and family leave, plus fertility support.
    - "Faire Fundays" (company-wide paid time off).
    - Annual learning grant for personal/professional development + unlimited LinkedIn Learning.
    - Fitness & wellbeing monthly credit.
    - Free access to Modern Health therapists and resources.
    - Charitable donation matching (up to $250/year).
- **Engineering Culture**: Described as tackling complex problems to build "one of the most ambitious technology platforms in retail." Strong emphasis on AI, search, and growth engineering. Many hires come from top tech companies (Google, Amazon, Uber, Shopify, Airbnb).
- **Career Growth**: A career framework is in place to allow employees to grow as leaders, hone their craft, or explore new disciplines.

## Sources
1. [faire.com - About](https://www.faire.com/about)
2. [faire.com - Careers](https://www.faire.com/careers)
3. [faire.com - Homepage](https://www.faire.com/)
4. [LinkedIn - Faire Jobs](https://www.linkedin.com/company/fairewholesale/jobs)
5. [LinkedIn - Faire Company Profile](https://www.linkedin.com/company/fairewholesale)

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