Faire

<div>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.</div>About the role
Are you passionate about using data and AI to shape the future of Faire's product features for small and medium businesses (SMBs)? If so, we want to talk to you! We're looking for a technical leader in our team to work closely with Data Scientists, Product Analysts and Software Engineers to support product launches and roadmaps by designing and building data capabilities that inform and drive insights. You will lead the path in using AI to boost productivity and transform how analytical engineering operates—leveraging AI to streamline data pipeline development and operations, improve data consumption workflows, and automate routine analytical tasks. In this role, you'll see a direct link between your work, company growth, and user satisfaction. You'll work with A tier players, work with one of the richest data sets in the world, use cutting-edge technology, and see your efforts affect products and SMBs regularly.
Join us and be part of a team that values data-driven innovation and excellence.
What You Will Do
The ideal candidate will possess a perfect blend of analytics and data engineering expertise, along with strong skills in developing and supporting large-scale, high-performance data storage and processing systems. They should have a proven track record of collaborating with key stakeholders to execute on company-wide data initiatives. 
<ul>
<li>Lead cross-team and/or multi-phase projects from design through implementation, fostering collaboration with cross-functional partners.</li>
<li>Lead the technical execution in building scalable data models and pipelines for a domain defining the architecture, feature requirements, roadmap.</li>
<li>Build data pipelines with rigorous approaches to data quality, validation, testing, and observability.</li>
<li>Redefine how we build, maintain, and scale data systems by embedding AI into our daily workflows.</li>
<li>Optimize processes for operational excellence in project management and system reliability.</li>
<li>Ensure security standards are met within data systems and workflows. </li>
<li>Ensure and promote data quality standards for accurate and reliable insights.</li>
<li>Embrace emerging technologies with enthusiasm.</li>
</ul>
Minimum qualifications
<ul>
<li>4+ years experience in analytics &amp; data engineering roles focused on data modeling, large-scale data processing, and tool development for analytics or data science use cases.</li>
<li>Demonstrated communication and leadership skills, with a history of initiating and steering successful projects across multiple stakeholders.</li>
<li>Production-level development experience in Python.</li>
<li>Strong SQL skills with demonstrable competencies in designing well-architected data models and optimizing query performance.</li>
<li>Deep experience and knowledge of data warehousing concepts, ETLs, big data technologies, and analytics platforms.</li>
<li>Experience with Airflow, Docker, DBT or similar analytics workflow tools.</li>
<li>BA/BS degree in Computer Science, Math, Physics, or a related technical field. </li>
</ul>
Salary Range
California: the pay range for this role is $196,000 to $269,500 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.<div>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
<ul>
<li>Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.</li>
<li>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.</li>
<li>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.</li>
<li>Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.</li>
<li>Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.</li>
</ul>
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 <a href="https://blog.faire.com/" rel="noopener noreferrer ugc" target="_blank">blog</a>.

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 <a href="https://docs.google.com/forms/d/e/1FAIpQLSczpI9me7nYKhunSC6AlagHKv75LHqfi-Qi2TP_3dpin0Uc9Q/viewform" rel="noopener noreferrer ugc" target="_blank">Accommodation Request Form</a> (<a href="https://bit.ly/faire-form)" rel="noopener noreferrer ugc" target="_blank">https://bit.ly/faire-form)</a>
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 <a href="https://www.faire.com/privacy" target="_blank" rel="noopener noreferrer ugc">Privacy Notice (https://www.faire.com/privacy)</a></div>

Senior Analytics Engineer - Retailer Growth

<div>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.</div>About this role:
Our Engineering organization owns the software that makes our marketplace work. The Data Platform group supports everyone at Faire who depends on data: Product Engineering, Data Science, Machine Learning, Analytics, Strategy, Finance, and Product. Our job is to make sure the data is there, it's right, and people can find it and query it without having to think about the plumbing underneath.
We are hiring a Staff Engineer to own that plumbing. Concretely, this means the path data takes out of our production databases (CockroachDB and MySQL) and into a place where analysts and data scientists can query it. Today that involves Fivetran, Kafka, Spark, and Airflow landing data in Snowflake and Databricks. It works, but it grew up over time and it shows. We want someone who can design the next version of it, build the hard parts personally, and bring the rest of the company along.
This is a hands-on role. You'll also be the person other teams come to when they need to know how data should move at Faire.
What you'll do:
<ul>
<li>
Set the technical direction for how data moves from production systems into our analytical stores, and own the roadmap to get there over the next couple of years.
</li>
<li>
Build the CDC and streaming ingestion layer: CockroachDB changefeeds and MySQL binlogs into Kafka, then into Iceberg tables on S3. You'll be responsible for the hard details like ordering, deduplication, late data, schema changes, and backfills.
</li>
<li>
Implement data contracts and quality checks throughout our platform
</li>
<li>
Put real ownership and SLAs on the datasets the business runs on, and wire quality checks into the platform with tools like Anomalo and Monte Carlo so we hear about broken data before a dashboard or a model does.
</li>
<li>
Run Airflow and Fivetran well, and have an opinion about what we should keep buying versus what we should build.
</li>
<li>
Own reliability for the platform: SLOs, on-call, incident reviews, and the follow-through so the same thing doesn't break twice.
</li>
<li>
Work with the senior engineers, data scientists, and analysts who depend on this platform, and lead the migration of existing pipelines onto the new one without breaking what they rely on.
</li>
<li>
Mentor the engineers around you. We want the team's data engineering practice to be better because you were here.
</li>
</ul>
Qualifications:
You've built and run data infrastructure that other teams depended on, at meaningful scale, and you've been the person setting direction for it, not just working on it.
<ul>
<li>
Deep experience with change data capture and streaming ingestion from operational databases through Kafka. You know what goes wrong with ordering, duplicates, snapshots, and schema evolution because you've dealt with it.
</li>
<li>
Hands-on experience with lakehouse architectures on an open table format. Iceberg on S3 is what we use, so that's especially valuable. You should be comfortable talking about partitioning, compaction, catalogs, and copy-on-write versus merge-on-read.
</li>
<li>
Strong Spark skills, and experience running Databricks and Snowflake against shared storage.
</li>
<li>
Experience with data quality and observability in practice, including data contracts, SLAs, and tools like Anomalo or Monte Carlo.
</li>
<li>
Experience operating Airflow at scale and working with managed ingestion like Fivetran.
</li>
<li>
Strong SQL, and good instincts for how to model data so analysts and data scientists can actually use it.
</li>
<li>
Solid Python plus at least one of Kotlin, Java, Scala, or Go. Experience shipping infrastructure on AWS with Terraform.
</li>
<li>
A working understanding of data governance: access control, PII, retention and deletion, lineage, and audit.
</li>
<li>
A track record of leading cross-team data initiatives and migrations, and of mentoring senior engineers.
</li>
<li>
You can explain a technical tradeoff to a leadership team and to a new grad, and you can get people who disagree with each other to a decision.
</li>
<li>
You take ownership of things that are broken or unowned, and you're willing to be on call for the systems you build.
</li>
<li>
Experience in a marketplace, e-commerce, or other transaction-heavy business is a plus.
</li>
</ul>
Technologies we use and teach:
<ul>
<li>
Python, Kotlin, SQL
</li>
<li>
Kafka, Fivetran, Airflow
</li>
<li>
S3, Apache Iceberg, Snowflake, Databricks, Apache Spark
</li>
<li>
AWS, Terraform, Kubernetes
</li>
<li>
CockroachDB, MySQL, Scylla and DynamoDB
</li>
</ul>
Salary range:
Canada: the pay range for this role is $216,000 to $297,000 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.<div>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
<ul>
<li>Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.</li>
<li>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.</li>
<li>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.</li>
<li>Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.</li>
<li>Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.</li>
</ul>
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 <a href="https://blog.faire.com/" rel="noopener noreferrer ugc" target="_blank">blog</a>.

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 <a href="https://docs.google.com/forms/d/e/1FAIpQLSczpI9me7nYKhunSC6AlagHKv75LHqfi-Qi2TP_3dpin0Uc9Q/viewform" rel="noopener noreferrer ugc" target="_blank">Accommodation Request Form</a> (<a href="https://bit.ly/faire-form)" rel="noopener noreferrer ugc" target="_blank">https://bit.ly/faire-form)</a>
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 <a href="https://www.faire.com/privacy" target="_blank" rel="noopener noreferrer ugc">Privacy Notice (https://www.faire.com/privacy)</a></div>

Staff Data Infrastructure Engineer

<div>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.</div>About this role:
Our Engineering organization owns the software that makes our marketplace work. The Data Platform group supports everyone at Faire who depends on data: Product Engineering, Data Science, Machine Learning, Analytics, Strategy, Finance, and Product. Our job is to make sure the data is there, it's right, and people can find it and query it without having to think about the plumbing underneath.
We are hiring a Staff Engineer to own that plumbing. Concretely, this means the path data takes out of our production databases (CockroachDB and MySQL) and into a place where analysts and data scientists can query it. Today that involves Fivetran, Kafka, Spark, and Airflow landing data in Snowflake and Databricks. It works, but it grew up over time and it shows. We want someone who can design the next version of it, build the hard parts personally, and bring the rest of the company along.
This is a hands-on role. You'll also be the person other teams come to when they need to know how data should move at Faire.
What you'll do:
<ul>
<li>
Set the technical direction for how data moves from production systems into our analytical stores, and own the roadmap to get there over the next couple of years.
</li>
<li>
Build the CDC and streaming ingestion layer: CockroachDB changefeeds and MySQL binlogs into Kafka, then into Iceberg tables on S3. You'll be responsible for the hard details like ordering, deduplication, late data, schema changes, and backfills.
</li>
<li>
Implement data contracts and quality checks throughout our platform
</li>
<li>
Put real ownership and SLAs on the datasets the business runs on, and wire quality checks into the platform with tools like Anomalo and Monte Carlo so we hear about broken data before a dashboard or a model does.
</li>
<li>
Run Airflow and Fivetran well, and have an opinion about what we should keep buying versus what we should build.
</li>
<li>
Own reliability for the platform: SLOs, on-call, incident reviews, and the follow-through so the same thing doesn't break twice.
</li>
<li>
Work with the senior engineers, data scientists, and analysts who depend on this platform, and lead the migration of existing pipelines onto the new one without breaking what they rely on.
</li>
<li>
Mentor the engineers around you. We want the team's data engineering practice to be better because you were here.
</li>
</ul>
Qualifications:
You've built and run data infrastructure that other teams depended on, at meaningful scale, and you've been the person setting direction for it, not just working on it.
<ul>
<li>
Deep experience with change data capture and streaming ingestion from operational databases through Kafka. You know what goes wrong with ordering, duplicates, snapshots, and schema evolution because you've dealt with it.
</li>
<li>
Hands-on experience with lakehouse architectures on an open table format. Iceberg on S3 is what we use, so that's especially valuable. You should be comfortable talking about partitioning, compaction, catalogs, and copy-on-write versus merge-on-read.
</li>
<li>
Strong Spark skills, and experience running Databricks and Snowflake against shared storage.
</li>
<li>
Experience with data quality and observability in practice, including data contracts, SLAs, and tools like Anomalo or Monte Carlo.
</li>
<li>
Experience operating Airflow at scale and working with managed ingestion like Fivetran.
</li>
<li>
Strong SQL, and good instincts for how to model data so analysts and data scientists can actually use it.
</li>
<li>
Solid Python plus at least one of Kotlin, Java, Scala, or Go. Experience shipping infrastructure on AWS with Terraform.
</li>
<li>
A working understanding of data governance: access control, PII, retention and deletion, lineage, and audit.
</li>
<li>
A track record of leading cross-team data initiatives and migrations, and of mentoring senior engineers.
</li>
<li>
You can explain a technical tradeoff to a leadership team and to a new grad, and you can get people who disagree with each other to a decision.
</li>
<li>
You take ownership of things that are broken or unowned, and you're willing to be on call for the systems you build.
</li>
<li>
Experience in a marketplace, e-commerce, or other transaction-heavy business is a plus.
</li>
</ul>
Technologies we use and teach:
<ul>
<li>
Python, Kotlin, SQL
</li>
<li>
Kafka, Fivetran, Airflow
</li>
<li>
S3, Apache Iceberg, Snowflake, Databricks, Apache Spark
</li>
<li>
AWS, Terraform, Kubernetes
</li>
<li>
CockroachDB, MySQL, Scylla and DynamoDB
</li>
</ul>
Salary range:
San Francisco &amp; New York: the pay range for this role is $246,500 to $339,000 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.<div>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
<ul>
<li>Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.</li>
<li>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.</li>
<li>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.</li>
<li>Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.</li>
<li>Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.</li>
</ul>
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 <a href="https://blog.faire.com/" rel="noopener noreferrer ugc" target="_blank">blog</a>.

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 <a href="https://docs.google.com/forms/d/e/1FAIpQLSczpI9me7nYKhunSC6AlagHKv75LHqfi-Qi2TP_3dpin0Uc9Q/viewform" rel="noopener noreferrer ugc" target="_blank">Accommodation Request Form</a> (<a href="https://bit.ly/faire-form)" rel="noopener noreferrer ugc" target="_blank">https://bit.ly/faire-form)</a>
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 <a href="https://www.faire.com/privacy" target="_blank" rel="noopener noreferrer ugc">Privacy Notice (https://www.faire.com/privacy)</a></div>

<div>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.</div>About the role
As a Senior Applied AI/ML Scientist on the Search team, you will help shape the technical vision, machine-learning algorithm strategy, and system design behind one of our most important growth levers: Search (the primary tool used by customers on any e-commerce site). You will advance real-time search and recommendation systems that power next-generation shopping experiences.
You’ll work at the frontier of algorithms, combining query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to return hyper-relevant, personalized products and brands for every user query.
This is a rare chance to influence the end-to-end personalized discovery experience at Faire within a high-scale, deeply multi-modal environment, while collaborating closely with a talented team of scientists and engineers.
What you’ll do
<ul>
<li>Build our next-generation Search ranking algorithms by integrating the latest advances in deep learning and machine learning to personalize the retailer discovery journey at Faire</li>
<li>Leverage LLM to extract multimodal signals (text, visual) to better profile users and their intents. </li>
<li>Partner closely with teams across Faire to experiment and improve the ML models for search ranking and beyond.</li>
<li>Design and productionize natural-language search and discovery systems so that intelligent agents can generate relevant and personalized collections, explain search results, and assist retailers with browsing, filtering, and evaluation.</li>
<li>Share best practices regarding deep learning model development, agent-workflow evaluation, and MLOps, and help teammates level up through code reviews and technical guidance.</li>
</ul>
You’re a great fit if you have…
<ul>
<li>5+ years of industry experience building large-scale ML models with business impact and shipping ML solutions to production, including 3+ years in search, recommendation, or ads ranking</li>
<li>A Master’s or PhD in Computer Science, Statistics, or a related STEM field.</li>
<li>Strong programming skills (Python, Java, or equivalent) and hands-on experience with deep-learning libraries (e.g., PyTorch) and big data technologies (e.g., Spark).</li>
<li>Deep understanding of machine learning best practices (e.g., training/serving, imbalanced data, A/B testing, feature engineering, and feature/model selection) and algorithms (e.g., user modeling, deep learning, and reinforcement learning) with applications in search, recommendation, and advertising domains.</li>
<li>A product-focused mindset and a bias toward execution—moving quickly from research papers to prototypes and production.</li>
<li>Excellent written and verbal communication skills and strong cross-functional influence that raise the technical bar beyond your immediate team.</li>
</ul>
Bonus points for…
<ul>
<li>Contributions to open-source ML libraries or peer-reviewed publications in ML/AI.</li>
<li>Industry experience developing and productizing LLM-based applications and systems in the search domain.</li>
<li>Industry experience building search and recommendation systems for e-commerce or two-sided marketplaces.</li>
<li>Experience using AI tools (e.g., Cursor, Claude Code, Codex) for code development and daily productivity.</li>
<li>Familiarity with Kotlin</li>
</ul>
Salary Range
San Francisco: the pay range for this role is $211,000 to $290,500 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.<div>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
<ul>
<li>Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.</li>
<li>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.</li>
<li>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.</li>
<li>Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.</li>
<li>Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.</li>
</ul>
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 <a href="https://blog.faire.com/" rel="noopener noreferrer ugc" target="_blank">blog</a>.

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 <a href="https://docs.google.com/forms/d/e/1FAIpQLSczpI9me7nYKhunSC6AlagHKv75LHqfi-Qi2TP_3dpin0Uc9Q/viewform" rel="noopener noreferrer ugc" target="_blank">Accommodation Request Form</a> (<a href="https://bit.ly/faire-form)" rel="noopener noreferrer ugc" target="_blank">https://bit.ly/faire-form)</a>
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 <a href="https://www.faire.com/privacy" target="_blank" rel="noopener noreferrer ugc">Privacy Notice (https://www.faire.com/privacy)</a></div>

Senior Applied AI/ML Scientist - Search Ranking

<div>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.</div>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 Applied AI/ML Scientists specialize in developing algorithmic solutions for notification and recommender systems, advertising attribution, and LTV predictions. We are dedicated to building machine learning models that help our customers thrive.
As a Senior Applied AI/ML Scientist on the Marketplace Quality team, you will own the modeling and measurement that keeps Faire's marketplace trustworthy for the hundreds of thousands of independent brands and retailers on it. Retailers need confidence that the price and the product they see on Faire are the real thing. That means matching Faire's catalog against messy external data at scale, detecting pricing and policy violations with calibrated confidence, and deciding which violations are worth acting on given a finite operations budget. You will work across structured and unstructured data (listing text, product images, external web listings, transaction history) using entity resolution, information extraction, multi-modal LLMs, calibrated classification, constrained optimization, and experimentation. You will drive projects end-to-end from framing through production and measurement, partnering closely with product, engineering, and our marketplace operations team.
Our team already includes experienced Applied AI/ML Scientists from Uber, Airbnb, Square, Facebook, and Pinterest. Faire will soon be known as a top destination for data scientists and machine learning engineers, and you will help take us there!
What you’ll do
<ul>
<li>Own applied ML projects end-to-end: framing the problem, building and shipping the model, and measuring impact on the marketplace.</li>
<li>Build and improve pricing-integrity models that compare Faire listings against external pricing signals and detect over- and under-pricing violations with a calibrated confidence bar.</li>
<li>Solve product matching and entity resolution at scale: link Faire's catalog to external listings using text and image embeddings, retrieval, and multi-modal LLMs, and build the match-quality and gating models that make downstream detection trustworthy.</li>
<li>Extract structured attributes from unstructured listing content (descriptions, images, third-party sources) to power detection and enrichment.</li>
<li>Turn model scores into action: design the targeting and prioritization logic that ranks violations by expected marketplace impact against the cost of a false positive, under a constrained human-review budget.</li>
<li>Build human-in-the-loop systems with our marketplace operations partners: design audits, generate training labels, set precision bars, and close the loop from review outcomes back into the models.</li>
<li>Design and analyze experiments for enforcement levers such as downranking, badging, and brand-facing remediation, and measure their effect on retailer trust and marketplace GMV.</li>
<li>Partner across product, engineering, operations, and analytics to turn models into shipped product and business impact.</li>
<li>Solve challenging problems related to a two-sided marketplace.</li>
</ul>
Qualifications 
<ul>
<li>3+ years of industry experience using machine learning to solve real-world problems.</li>
<li>Experience with relevant business problems (e-commerce, marketplaces, catalog and content quality, search, or personalization).</li>
<li>Experience with relevant technical methods (deep learning and LLMs, computer vision, information extraction, entity resolution, ranking, and/or experimentation and causal inference).</li>
<li>Strong programming skills.</li>
<li>An excitement and willingness to learn new tools and techniques.</li>
<li>The ability to drive a project end-to-end and lead model development with limited supervision.</li>
<li>Strong communication skills and the ability to work in a highly cross-functional team.</li>
</ul>
Great to Haves:
<ul>
<li>Highly recommended: Master's or PhD in Computer Science, Statistics, or related STEM fields.</li>
<li>Previous experience with catalog quality, product attribute extraction, computer vision for e-commerce imagery, or search and discovery for a two-sided platform.</li>
<li>Experience building and validating LLM evaluation pipelines, including prompt iteration against labeled data and human-in-the-loop workflows.</li>
</ul>
Salary Range
San Francisco: the pay range for this role is $211,000 to $290,500 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.<div>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
<ul>
<li>Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly.</li>
<li>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.</li>
<li>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.</li>
<li>Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work.</li>
<li>Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success.</li>
</ul>
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 <a href="https://blog.faire.com/" rel="noopener noreferrer ugc" target="_blank">blog</a>.

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 <a href="https://docs.google.com/forms/d/e/1FAIpQLSczpI9me7nYKhunSC6AlagHKv75LHqfi-Qi2TP_3dpin0Uc9Q/viewform" rel="noopener noreferrer ugc" target="_blank">Accommodation Request Form</a> (<a href="https://bit.ly/faire-form)" rel="noopener noreferrer ugc" target="_blank">https://bit.ly/faire-form)</a>
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 <a href="https://www.faire.com/privacy" target="_blank" rel="noopener noreferrer ugc">Privacy Notice (https://www.faire.com/privacy)</a></div>

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