How to Apply to Faire

10 min read Last updated March 7, 2026 78 open positions
Blake Crosley
Blake Crosley Researched using publicly available information, hiring data, and ATS analysis.

Key Takeaways

  • Before applying, spend 30 minutes exploring Faire's marketplace as a retailer (you can browse faire.com) — understanding the product experience will dramatically improve your application and interview performance compared to candidates who've never used the platform
  • Tailor your resume with exact keywords from Faire's job descriptions, especially domain-specific terms like 'listing quality,' 'search algorithms,' 'marketplace,' 'fraud detection,' and 'net terms' to ensure Greenhouse surfaces your application to recruiters
  • Prepare a compelling, specific answer to 'Why Faire?' that goes beyond generic startup enthusiasm — reference the independent retail mission, the technical complexity of B2B marketplace problems, or a personal connection to small business
  • For technical roles, practice applied data science and ML problems using marketplace-relevant scenarios (recommendation systems, ranking algorithms, fraud scoring) rather than LeetCode-style algorithmic puzzles
  • Quantify every major accomplishment on your resume with metrics that demonstrate business impact — Faire's culture prizes measurable outcomes, and vague descriptions signal misalignment with their operating style
  • Research Faire's recent product launches, geographic expansion, and financial products (like Faire Direct or net-60 terms) so you can engage substantively with interviewers about the company's strategic direction
  • Submit a complete Greenhouse application with all optional fields filled in, a clean single-column PDF resume, and thoughtful responses to any screening questions — partial or rushed applications are easily filtered out

About Faire

Faire is a B2B wholesale marketplace that connects independent retailers with unique brands, fundamentally reshaping how small businesses discover and purchase inventory. Founded in 2017 by former Square executives, the company has grown into one of the most valuable private technology companies in the world, serving hundreds of thousands of retailers and brands across North America, Europe, and beyond. Faire's platform uses sophisticated machine learning algorithms to match retailers with products their customers are most likely to buy — effectively giving independent shops the data-driven merchandising power that was once exclusive to big-box chains. The company's culture is deeply rooted in entrepreneurial thinking, data-driven decision-making, and a genuine mission to level the playing field for small businesses. Employees frequently describe the environment as intellectually rigorous yet collaborative, with a strong emphasis on ownership and impact. Faire operates with a lean startup mentality despite its scale, meaning individual contributors often have outsized influence on product direction and company strategy. What draws top talent to Faire is the rare combination of meaningful mission and technical complexity. The platform's recommendation engines, fraud detection systems, financial products (like Faire's net-60 payment terms), and search algorithms present genuinely challenging problems at scale. For candidates who want to work on problems that matter — helping independent businesses thrive against corporate retail giants — while pushing the boundaries of machine learning, fintech, and marketplace dynamics, Faire represents one of the most compelling opportunities in the private technology sector.

Application Process

  1. 1
    Identify Your Role on Faire's Careers Page

    Visit faire.com/careers and browse their approximately 78+ open openings across engineering, data science, product, finance, operations, and people teams. Faire organizes roles by department and location, so filter carefully — some roles are remote-eligible while others are tied to specific offices (San Francisco, Toronto, or international hubs). Pay close attention to the seniority level in each title, as Faire distinguishes clearly between Senior, Staff, and Lead-level expectations.

  2. 2
    Submit Your Application Through Greenhouse

    Faire uses Greenhouse as its applicant tracking system, so all applications flow through structured submission forms. You'll typically upload your resume, provide contact details, and answer role-specific screening questions. Some roles — particularly in data science, product, and strategic finance — may include short-answer prompts designed to assess your analytical thinking before you ever reach a recruiter.

  3. 3
    Recruiter Phone Screen

    If your application advances, a Faire recruiter will schedule a 30-45 minute introductory call. Expect questions about your motivation for joining Faire specifically, your understanding of the wholesale marketplace model, and a high-level walkthrough of your relevant experience. Recruiters at Faire commonly probe for mission alignment — they want to know you understand and care about the independent retail ecosystem.

  4. 4
    Hiring Manager or Technical Screen

    The next stage typically involves a deeper conversation with the hiring manager or a senior team member. For technical roles like ML Engineer or Data Scientist, this often includes a technical screen — possibly a take-home assignment or live coding exercise focused on real-world problems similar to what Faire's teams actually solve (e.g., recommendation quality, listing ranking, fraud scoring). For non-technical roles, expect a case study or scenario-based discussion relevant to Faire's business.

  5. 5
    Virtual or On-Site Interview Loop

    Faire's interview loops typically consist of 4-6 sessions conducted over a half-day or full day. These are structured to evaluate technical depth, cross-functional collaboration, and cultural alignment. You'll commonly meet with potential teammates, cross-functional partners, and at least one senior leader. Each interviewer typically evaluates a specific competency using a structured scorecard within Greenhouse.

  6. 6
    Debrief and Decision

    After your interview loop, the hiring team convenes for a structured debrief — a hallmark of Greenhouse-powered hiring processes where each interviewer submits independent feedback before the group discussion. Faire reportedly values consensus-driven decisions, meaning strong signals from multiple interviewers carry significant weight. This stage typically takes 3-7 business days.

  7. 7
    Offer and Negotiation

    Successful candidates receive a comprehensive offer that typically includes base salary, equity in the form of stock options (given Faire's private status), and benefits. Faire's recruiters commonly walk candidates through the equity component in detail, explaining vesting schedules and the company's growth trajectory. Given the competitive talent market for ML, fintech, and marketplace expertise, there is often room for thoughtful negotiation.

Resume Tips for Faire

critical

Lead with Marketplace, Fintech, or ML Impact Metrics

Faire sits at the intersection of three complex domains: marketplace dynamics, financial technology, and machine learning. Your resume should immediately signal expertise in at least one of these areas with quantified outcomes. Instead of 'Improved recommendation system,' write 'Increased marketplace GMV 18% by redesigning product recommendation algorithm serving 200K+ retailers.' Faire's hiring teams are steeped in metrics culture — vague claims without numbers will fall flat.

critical

Mirror Faire's Exact Role Terminology in Your Resume

Greenhouse parses resumes against role-specific keywords configured by Faire's recruiting team. Study the job description carefully and incorporate their precise language — terms like 'listing quality,' 'search algorithms,' 'fraud detection,' 'net terms,' 'wholesale marketplace,' and 'retailer experience' appear frequently across Faire's postings. If you've worked on analogous problems using different terminology, explicitly bridge the gap (e.g., 'product ranking optimization (analogous to listing quality scoring)').

critical

Demonstrate Small Business or Retail Ecosystem Awareness

Faire's mission centers on empowering independent retailers and emerging brands. Candidates who demonstrate genuine understanding of — or personal connection to — the independent retail ecosystem stand out. If you've worked with SMBs, retail technology, or wholesale supply chains, feature that experience prominently. Even tangential experience (e.g., building tools for small business owners) signals mission alignment that Faire's recruiters actively screen for.

recommended

Highlight Cross-Functional Collaboration and Ownership

Faire operates with relatively flat, cross-functional teams where engineers work closely with product managers, data scientists collaborate with operations, and finance partners embed with business units. Structure your bullet points to show not just what you built, but who you partnered with and what business outcome resulted. Phrases like 'Partnered with product and engineering to...' or 'Led cross-functional initiative across data science, ops, and risk teams' resonate strongly.

recommended

Use Clean, ATS-Friendly Formatting for Greenhouse

Greenhouse handles standard resume formats well but can struggle with multi-column layouts, text boxes, headers/footers containing critical information, and heavily designed templates. Use a single-column format with clear section headers (Experience, Education, Skills), standard fonts, and submit as a PDF unless the application specifically requests .docx. Ensure your name and contact information appear in the main body text, not in a header that Greenhouse's parser might skip.

recommended

Showcase Scale and Complexity Appropriate to Role Level

Faire's job titles clearly delineate seniority — Senior, Staff, Lead, Head of — and each carries specific scope expectations. For Staff-level roles (like Staff Product Manager, Search Algorithms), emphasize multi-team influence, architectural or strategic decisions, and ambiguous problem spaces you've navigated. For Senior-level roles, focus on deep individual contribution with growing scope. Misalignment between your resume's demonstrated scope and the role's level is a common reason for early-stage rejections.

nice_to_have

Include Relevant Technical Stack and Tools

For technical roles, Faire commonly works with Python, SQL, and modern ML frameworks. Their data infrastructure likely involves tools common in high-growth marketplaces: Spark, Airflow, dbt, and cloud platforms like AWS or GCP. List your technical proficiencies in a dedicated skills section and weave them naturally into your experience bullets. For finance and operations roles, mention experience with tools like Netsuite, Anaplan, or similar enterprise systems that companies at Faire's stage typically use.

nice_to_have

Keep It to One Page (Two Maximum for 10+ Years)

Faire's recruiters review a high volume of applications through Greenhouse's candidate pipeline view, where concise, scannable resumes perform best. Aim for one page if you have fewer than ten years of experience, and ensure even a two-page resume front-loads the most relevant experience. Greenhouse displays parsed resume data in a structured format, so excessive length creates noise rather than signal for reviewers.

ATS System: Greenhouse

Greenhouse is a structured hiring platform used by Faire to manage its entire recruitment pipeline, from application intake through offer. It parses uploaded resumes to extract contact information, work history, education, and skills, then scores and organizes candidates against role-specific criteria configured by Faire's talent team. Greenhouse also powers Faire's structured interview scorecards, ensuring consistent evaluation across all candidates.

  • Submit your resume as a clean PDF with a single-column layout — Greenhouse's parser handles this format most reliably and avoids the formatting errors common with multi-column designs
  • Place your name, email, phone number, and LinkedIn URL in the main document body rather than in headers or footers, which Greenhouse may not parse correctly
  • Mirror exact keywords from Faire's job description — Greenhouse allows recruiters to filter and search candidates by specific terms like 'marketplace,' 'ML,' 'fraud,' or 'strategic finance'
  • Complete every field in the Greenhouse application form, including optional ones — partially completed applications are commonly deprioritized in recruiter workflows
  • Avoid using images, charts, icons, or graphics in your resume — Greenhouse cannot parse visual elements, meaning that information is effectively invisible to the system and to recruiters doing keyword searches
  • Use standard section headers like 'Experience,' 'Education,' and 'Skills' — non-standard creative headers can confuse Greenhouse's resume parser and result in misclassified information
  • If reapplying to a different role at Faire, update your resume in Greenhouse rather than creating a duplicate profile — Greenhouse tracks candidate history, and a tailored, updated application looks more intentional than a generic resubmission

Complete Greenhouse Resume Guide →

Interview Culture

Faire's interview process reflects the company's core operating principles: data-driven rigor, intellectual curiosity, and deep mission alignment.

Candidates commonly report a structured, well-organized experience — a byproduct of Greenhouse's scorecard system and Faire's investment in hiring as a craft. For technical roles such as Senior Data Scientist, ML Engineer, or Staff Product Manager, expect a multi-round process that typically spans 2-4 weeks from first contact to offer. The initial recruiter screen focuses heavily on motivation and mission fit — interviewers want to understand why you're drawn to the wholesale marketplace space and the specific challenges of connecting independent retailers with brands. This is not a throwaway question at Faire; candidates who demonstrate superficial interest in the mission are commonly filtered out at this stage. Technical evaluations vary by role but tend to emphasize applied problem-solving over abstract algorithmic puzzles. Data scientists and ML engineers may encounter take-home assignments involving real-world-like datasets (think listing quality scoring or recommendation relevance), followed by live discussions where you defend your methodology and explore extensions. Product managers should prepare for case studies grounded in Faire's actual product challenges — search ranking, marketplace liquidity, seller quality signals — and be ready to articulate how they'd use data to make decisions. The full interview loop typically involves 4-6 sessions, including at least one focused on behavioral and leadership competencies. Faire values 'builder' mentality and entrepreneurial ownership, so expect questions probing how you've operated in ambiguous environments, driven outcomes without full authority, and made trade-offs with imperfect information. Cross-functional awareness matters: you'll likely interview with people outside your immediate function to assess collaboration skills. Culture fit at Faire means intellectual humility, bias toward action, comfort with rapid iteration, and genuine enthusiasm for empowering small businesses. Come prepared with specific examples that demonstrate these qualities, and don't be surprised if interviewers share candid details about the challenges they're currently facing — this transparency is part of Faire's evaluation of whether candidates thrive in a high-ownership, high-transparency environment.

What Faire Looks For

  • Deep analytical rigor — Faire is a data-obsessed organization where every team, from product to finance to operations, is expected to make decisions grounded in quantitative evidence
  • Mission-driven motivation — genuine enthusiasm for leveling the playing field for independent retailers and emerging brands, not just interest in working at a high-growth startup
  • Builder mentality and entrepreneurial ownership — willingness to operate in ambiguous problem spaces, define your own scope, and drive outcomes end-to-end without waiting for direction
  • Marketplace-specific expertise — understanding of two-sided marketplace dynamics including supply-demand balancing, network effects, liquidity challenges, and quality signal design
  • Cross-functional collaboration skills — ability to partner effectively across engineering, data science, product, operations, and finance teams in a relatively flat organizational structure
  • Technical depth appropriate to role level — Staff-level candidates must demonstrate architectural thinking and multi-team influence, while Senior candidates should show deep individual contribution with expanding scope
  • Intellectual humility and rapid iteration — comfort with being wrong, incorporating feedback quickly, and shipping imperfect-but-improving solutions rather than waiting for perfection
  • Customer empathy for both sides of the marketplace — understanding the distinct needs, constraints, and motivations of both independent retailers and wholesale brands

Frequently Asked Questions

How long does Faire's hiring process typically take from application to offer?
Based on candidate reports, Faire's hiring process typically spans 3-5 weeks from initial application to offer, though this varies by role complexity and seniority. The recruiter screen usually happens within 1-2 weeks of application if you're selected, followed by a technical screen or hiring manager call within another week. The full interview loop is commonly scheduled 1-2 weeks after the screen. Senior and Staff-level roles, or those requiring specialized expertise (like ML engineering or tax leadership), may take slightly longer due to the involvement of more senior decision-makers. Following up with your recruiter after each stage is appropriate and generally welcomed.
Does Faire require a cover letter with applications?
Faire's Greenhouse application forms typically do not require a cover letter, but many roles include an optional field or short-answer questions that serve a similar purpose. If a cover letter field is available, use it strategically — don't rehash your resume, but instead explain your specific interest in Faire's mission of empowering independent retailers and how your experience maps to the role's core challenges. A concise, mission-aligned cover letter can differentiate you from equally qualified candidates, particularly for non-technical roles like Strategic Finance, Operations, and People team positions where communication skills are directly evaluated.
What experience level does Faire typically hire for?
Faire's current openings skew toward mid-senior to senior levels, with titles frequently including 'Senior,' 'Staff,' 'Lead,' and 'Head of' designations. This is typical for a company at Faire's growth stage — they've moved past the early-stage phase of hiring generalists and now seek specialists with demonstrated depth. That said, some roles in operations, recruiting, and analytics may be accessible to candidates with 3-5 years of experience. If you're earlier in your career, focus your application on roles that align precisely with your strongest skills and demonstrate outsize impact relative to your experience level.
Does Faire offer remote work options?
Faire has adopted a flexible work model that varies by role and team. Some positions are listed as remote-eligible, while others are tied to specific office locations including San Francisco and Toronto. The company has publicly discussed its approach to distributed work, and many roles — particularly in engineering, data science, and product — appear to offer significant remote flexibility. Check each job listing carefully for location requirements, as Greenhouse filters often allow you to sort by remote eligibility. During your recruiter screen, clarify the specific in-office expectations for your role, as team-level norms may differ from company-wide policy.
How should I prepare for a data science or ML interview at Faire?
Faire's data science and ML interviews emphasize applied, business-relevant problem-solving over textbook algorithms. Prepare by studying marketplace-specific ML challenges: recommendation systems, search ranking, listing quality scoring, fraud detection, and demand forecasting. Be ready to discuss your end-to-end approach — from problem framing and feature engineering through model selection, evaluation, and production deployment. Faire commonly uses take-home assignments that simulate real-world scenarios, so practice working with messy datasets under time constraints and presenting your findings clearly. Brush up on experimental design and A/B testing methodology, as Faire's data-driven culture means every ML model's impact is rigorously measured.
What should I know about Faire's business before interviewing?
Understanding Faire's two-sided marketplace model is essential. Faire connects independent retailers (buyers) with wholesale brands (sellers), offering features like curated product recommendations, net-60 payment terms, and free returns on opening orders that reduce risk for retailers. The platform earns revenue through commissions on transactions. Familiarize yourself with Faire Direct (which lets brands bring their existing retail customers onto Faire's payment and logistics infrastructure), their international expansion into European markets, and the competitive landscape including other B2B wholesale platforms. Browse faire.com to understand the retailer experience firsthand, and read their blog for insights into recent product launches and company philosophy.
How does Faire's Greenhouse ATS affect my application, and how can I optimize for it?
Greenhouse is Faire's applicant tracking system, and it plays a central role in how your application is organized, searched, and evaluated. When you upload your resume, Greenhouse parses it into structured fields — if your formatting is non-standard (multi-column, graphics-heavy, or using unusual section headers), critical information may be lost or misclassified. Use a clean, single-column PDF format with standard section headers. More importantly, Faire's recruiters use Greenhouse's search and filter functions to find candidates matching specific criteria, so incorporating exact terminology from the job description (not synonyms or abbreviations) increases your visibility. Complete every field in the application form, as incomplete profiles are easily filtered out in bulk screening.
Can I apply to multiple roles at Faire simultaneously?
Yes, Greenhouse supports multiple applications, and Faire can see your full application history. However, apply strategically — submitting to many unrelated roles signals unfocused interest and can work against you. If two or three roles genuinely align with your experience (for example, a Senior Data Scientist position and an ML Engineer position), tailor each application's resume and screening question responses to that specific role's requirements. Your recruiter may also suggest alternative roles during the screening process if they see a stronger fit elsewhere, so being open to that conversation demonstrates flexibility and trust in the process.
What is Faire's interview format for non-technical roles like finance, operations, or people team positions?
Non-technical roles at Faire typically follow a structured loop that includes a recruiter screen, a hiring manager deep-dive, a case study or scenario-based exercise, and cross-functional interviews. For Strategic Finance and Operations roles, expect analytical case work that tests your ability to model business scenarios, synthesize data, and make recommendations under uncertainty — reflecting the quantitative rigor Faire expects across all functions. People team and recruiting roles will likely include situational and behavioral interviews probing how you've built programs, managed stakeholders, and scaled processes in high-growth environments. In all cases, prepare specific examples that demonstrate ownership, data-informed decision-making, and the ability to operate effectively across teams.

Sample Open Positions

Check Your Resume Before Applying → View 78 open positions at Faire

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Sources

  1. Faire Careers Page — Faire
  2. Faire Company Overview and Product Information — Faire
  3. Faire Interview Reviews and Company Ratings — Glassdoor
  4. Greenhouse Applicant Tracking System — How It Works — Greenhouse Software
  5. Faire Blog — Company Culture and Product Updates — Faire