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JI
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- Full-time
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Process Engineer, Production
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Faire

Senior Product Engineer - Listing Quality

Kitchener, ON, Canada
Toronto, ON, Canada

Canada: the pay range for this role is $156,000 - $214,500 per year.

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Job details

Pay: Canada: the pay range for this role is $156,000 - $214,500 per year.
Experience: 5+ years of experience
Posting language: English
Posted: Nov 3, 2026

Original 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.

Why Listing Quality at Faire?

Our mission in the Brand pillar is to make it easy for Brands to create high-quality product listings on Faire, keep them up to date, and get them in front of retailers. Having access to well-curated catalogs of products lets Main Street retailers compete with big-box stores, and we’re responsible for the first step in that journey.

As a Senior Product Engineer on the Listing Quality team, you’ll make every product on Faire look and read its best. We use computer vision and LLMs to improve hero images, crops and product descriptions across millions of listings, and we prove the impact through online experiments.

About this role:

You’ll partner closely with Brand Data Science. They own model quality. You own getting model outputs into the product reliably, at catalog scale, and measurably. When it’s faster to test an idea yourself, you do: tune the prompt, build the eval, and run the experiment.

This is an ideal role for engineers who want to work where machine learning meets production systems, and who care as much about whether retailers click as whether the job succeeded. You like turning a data scientist’s prototype into something that runs every day without anyone thinking about it, and you’re just as happy building the first prototype yourself.

You’re entrepreneurial and data-driven, with a strong product sense, and you’re excited about learning how our customers’ businesses work and what they need in order to succeed. You balance your excitement for building features with a focus on their long-term maintainability. You want to use technology to help your local independent retailers and brands succeed, and to experiment with the best AI productivity tools on the market to accelerate customer impact.

What you’ll do:

Build and own the backend services and data paths that take model-generated enhancements from batch pipelines into the live product
Design the infrastructure that makes catalog-scale generation dependable: backfills, freshness and staleness detection, coverage monitoring, and versioning of generated content
Shorten the loop from data science prototype to production experiment through clean handoff contracts, output auditing tools and evaluation hooks
Ship changes behind experiment flags, and own test plans, launch readiness and post-launch health
Make cost, latency and quality tradeoffs when running LLM and vision workloads over large datasets
Mentor fellow engineers on both technical and product judgement

Qualifications:

You may be a great fit if you have:

5+ years of experience
Proficiency in at least one of Java, Kotlin, or JavaScript
Comfort with agentic coding tools
Familiarity with HTML, CSS, TypeScript, and frameworks/libraries like React and Next.js
Experience building or operating data pipelines (Airflow or similar, a warehouse like Snowflake)
Comfort working with ML or LLM outputs in production. You don’t need to train models, but you understand how they fail
Fluency with experimentation, including designing a rollout and telling a real result from noise
A bachelor’s degree in Computer Science/Software Engineering or equivalent industry experience
A love for technology, and an insatiable curiosity for new tools to solve real problems

Don’t meet every qualification? We know great candidates come from many different backgrounds and experiences. If you’re excited about the role, we’d encourage you to apply.

Technologies we use & teach:

Experience with similar technologies is welcome - you don’t need experience with our exact stack.

Frontend: React, NextJS, JavaScript
Backend: Kotlin, Java, Guice, Jersey, Hibernate, JUnit
Datastores: MySQL, CockroachDB
Infrastructure & Cloud: AWS
APIs & Data: HTTP, JSON, Protocol Buffers

Salary range:

Canada: the pay range for this role is $156,000 - $214,500 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

Flexible paid time off, plus company-wide recharge days
Paid parental leave up to 16 weeks
Comprehensive health coverage, with options varying by location
Fertility and family-building benefits through Carrot, including a lifetime reimbursement allowance
Mental health support and coaching through Modern Health
Stipends to support your professional development, wellness, and work from home needs
Employer-sponsored retirement plan, dependent on country of employment

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 ()

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)

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More about this job

Responsibilities

You will build and maintain backend services and data paths to integrate model-generated enhancements into the live product at scale. Additionally, you will design infrastructure for catalog-scale generation and lead experimentation to optimize product quality.

Requirements

The role requires 5+ years of experience with proficiency in Java, Kotlin, or JavaScript and experience building data pipelines. Candidates should have a bachelor's degree in Computer Science or equivalent and familiarity with modern web frameworks and ML production environments.

Skills

Java
Kotlin
JavaScript
TypeScript
React
Next.js
Machine Learning
LLMs
Computer Vision
Data Pipelines
Airflow
Snowflake
Backend Development
Experimentation
System Architecture
Mentorship

Benefits

Flexible paid time off
Company-wide recharge days
Paid parental leave
Comprehensive health coverage
Fertility and family-building benefits
Mental health support and coaching
Professional development stipend
Wellness stipend
Work from home stipend
Equity

Visa sponsorship

Not detected in the job text

Keywords

Java
Kotlin
JavaScript
TypeScript
React
Next.js
Machine Learning
LLM
Computer Vision
Airflow
Snowflake
MySQL
CockroachDB
AWS
Backend
Data Pipelines
Experimentation
Software Engineering
Product Engineering
API
JSON
Protocol Buffers
Hibernate
Jersey
Guice
JUnit
Scalability
Infrastructure
Data Science
Retail Technology

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