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 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 recommender systems, spend optimization, lifetime value (LTV) predictions, and much more. Our ultimate goal is to empower local retail businesses with the tools they need to succeed.
At Faire, the Data team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive.
As an Applied AI/ML Scientist tech lead, you will own vision, strategy, and execution for a set of problems that power Faire's two-sided marketplace, connecting hundreds of thousands of independent brands and retailers. Because our users are businesses, there is a wealth of information about them that ML models can use to personalize their experience, grow their success, and keep the marketplace high quality and trustworthy. You will work across structured and unstructured data using methods that range from personalization and recommendations to causal inference, lifetime-value modeling, information extraction, and LLMs. You will act as a lead across multiple cross-functional workstreams and mentor or manage other scientists on the team.
Our team already includes experienced Data Scientists from Uber, Airbnb, Square, Facebook, and Pinterest. Faire will soon be known as a top destination for Applied AI/ML Scientists, and you will help take us there!
What you’ll do
<ul>
<li>Drive data science vision, strategy, and execution end-to-end, and act as a pod lead across cross-functional workstreams.</li>
<li>Develop personalized recommendation, retrieval, and ranking models, and build content and retailer-level embeddings to power better discovery and exploration experiences.</li>
<li>Optimize marketing, acquisition, and incentive spend through targeting and personalization, and use experimentation and causal inference to measure the effectiveness of spend levers.</li>
<li>Predict lifetime value to prioritize sales and acquisition effort and to personalize the new-user experience, even in a user's first session.</li>
<li>Improve cold-start recommendations and exploration so that new users and new selection find the right audience quickly.</li>
<li>Extract insights from internal and external data (e.g. reviews, search behavior, referrals, and third-party sources) to enrich leads and power personalization.</li>
<li>Use deep learning, multi-modal LLMs, and human-in-the-loop training to understand listings and content, extract structured attributes, and detect issues with high accuracy.</li>
<li>Build detection, enforcement, and quality systems that reduce bad experiences in the marketplace (e.g. counterfeits, policy violations, poor service quality), using levers such as downranking and human-in-the-loop targeting.</li>
<li>Re-engage users through personalized marketing and identify gaps and opportunities that drive increased engagement.</li>
<li>Mentor or manage Senior Applied AI/ML Scientists and Analytics Engineers.</li>
<li>Solve challenging problems related to a two-sided marketplace.</li>
</ul>
Qualifications
<ul>
<li>5+ years of industry experience using machine learning to solve real-world problems.</li>
<li>Experience with relevant business problems (e-commerce, marketplaces, growth, personalization, incentives, or trust and quality).</li>
<li>Experience with relevant technical methods (causal inference, predictive/LTV modeling, recommendations, information extraction, entity resolution, and/or deep learning and LLMs).</li>
<li>Strong programming skills.</li>
<li>An excitement and willingness to learn new tools and techniques.</li>
<li>Experience as a tech lead, mentoring other scientists or machine learning engineers, and the ability to set team strategy and lead model development without 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>Experience as a tech lead manager or people manager of applied ML / data science teams.</li>
<li>Previous experience in marketplace growth, incentive optimization, or trust and quality for a two-sided platform.</li>
<li>Previous experience with deep learning or language models.</li>
</ul>
Salary Range
San Francisco: 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.<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 Applied AI/ML Scientist - Brand Growth & Marketplace Quality

<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>Note: This role can also be performed remotely for candidates located in Arizona, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Illinois, Indiana, Kentucky, Maine, Maryland, Massachusetts, Michigan, Minnesota, Missouri, Nevada, New Hampshire, New Jersey, New Mexico, New York, North Carolina, Ohio, Oregon, Pennsylvania, Rhode Island, Tennessee, Texas, Utah, Virginia, Washington, or Wisconsin.
About this role
As the Senior Staff Machine Learning Platform Engineer, you will own the technical vision and evolution of Faire’s ML platform. You will set standards, influence org-wide architecture, and lead complex, cross-functional initiatives that unlock data science velocity at scale.  This role will also be key to adapting ML workflows to take advantage of modern AI productivity tools. You won’t just build models, you will architect the systems that allow those models to help tens of thousands of small retailers compete and grow their local businesses.
What You Will Do
<ul>
<li>Define and drive the long-term architecture of Faire’s ML platform including training, inference, feature management, governance</li>
<li>Establish company-wide standards for code quality, testing, MLOps (CI/CD), experimentation, model lifecycle management, and observability</li>
<li>Lead adoption and advanced use of Unity Catalog, multi-workspace strategies, and data/ML mesh patterns</li>
<li>Architect highly scalable ML workflows using Spark, Delta Lake, and MLflow</li>
<li>Optimize performance, reliability, and cost of the ML platform</li>
<li>Evaluate and integrate emerging Databricks features</li>
<li>Stay ahead of the curve by engaging with the latest developments in machine learning and AI</li>
<li>Serve as senior ML technical advisor to Faire’s data science and production engineering teams </li>
<li>Represent Faire at ML conferences and meetups</li>
<li>Mentor ML engineers and raise the overall bar for Machine Learning at Faire</li>
</ul>
What it takes
<ul>
<li>10-12 years of experience building and improving large-scale ML or data platforms.</li>
<li>A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field.</li>
<li>Deep expertise in Databricks lakehouse architecture, including governance via Unity catalog, orchestration via Workflows, and cost optimization</li>
<li>Proven ability to design systems that support multiple data science teams and production workloads</li>
<li>Strong background in distributed systems, ML infrastructure, and cloud architecture.</li>
<li>Demonstrated technical leadership across teams and orgs; ability to influence without authority</li>
<li>Experience integrating LLM workflows into enterprise platforms is a plus</li>
<li>Previous contributions to open source ML Infrastructure projects or research publications is a very strong plus</li>
</ul>
Tech Stack
Faire uses a modern cloud based tech stack.  For this role, you’ll want to be proficient with the following:
<table>
<tbody>
<tr>
<td>
Category
</td>
<td>
Technologies
</td>
</tr>
<tr>
<td>
Languages
</td>
<td>
Python, SQL, Kotlin
</td>
</tr>
<tr>
<td>
ML Frameworks
</td>
<td>
PyTorch, PySpark, MLFlow 
</td>
</tr>
<tr>
<td>
Big Data &amp; Processing
</td>
<td>
Spark, Kafka, Databricks, Snowflake, Fivetran, Iceberg, Unity Catalog, Datadog, Airflow, Cockroach DB, MySQL
</td>
</tr>
<tr>
<td>
Cloud &amp; Infrastructure
</td>
<td>
AWS, S3, SageMaker, Kubernetes, Docker, GitHub Actions, Terraform
</td>
</tr>
<tr>
<td>
Generative AI
</td>
<td>
Claude Sonnet 4.5, ChatGPT 5.2
</td>
</tr>
</tbody>
</table>
Salary Range
California: the pay range for this role is $295,000 to $405,500 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 Staff Machine Learning Platform 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 the role
Search is how retailers do their jobs on Faire. Wholesale queries and retailer expectations look different from consumer e-commerce and the right product depends on the store's category, price point, and aesthetic. When we get it wrong, it costs real money.
The Search algorithms team owns everything between the click on the search bar and the final ranker: typeahead and empty-state suggestions, query understanding, retrieval across five-plus independent sources, relevance modeling, and result-page surfaces like carousels and refinements. Within our scope, scientists own components outright: when you own query understanding here, you own the models, the roadmap, and the metrics.
You'll work across the full modern search stack: transformer-based embedding retrieval serving live traffic, LLMs powering query understanding and query rewriting, fine-tuned vision-language models scoring relevance, and graph-based retrieval — with generative retrieval and semantic IDs on the horizon.
What you'll do
<ul>
<li>Contribute to the next-generation Search engine, integrating LLMs, query understanding, dense vector retrieval, deep personalization embeddings, multi-stage ranking, and reinforcement learning to serve personalized product feeds with &lt;100ms latency.</li>
<li>Own one or more search components end to end: problem framing, modeling, production code, experiment design, and the call on what to build next.</li>
<li>Ship to live traffic and let A/B tests, not opinions, settle what works.</li>
<li>Raise the team's bar through design reviews, pairing, and honest post-mortems</li>
</ul>
You're a great fit if you have
<ul>
<li>3+ years building production ML systems, with meaningful time in search, recommendations, or another retrieval-and-relevance domain.</li>
<li>Shipped models that served real traffic, and owned the experiments that proved (or disproved) their value.</li>
<li>Depth somewhere in the modern retrieval stack — dual encoders and ANN serving, LLM-based query understanding, learning-to-rank fundamentals — and the ability to pick up the rest. </li>
<li>Strong Python and the engineering chops to take your own models to production.</li>
<li>Clear communication with scientists, engineers, and PMs: you make a crisp case for your ideas and update quickly when someone has a better one.</li>
<li>Excellent product judgment to connect customer and business context to technical decisions</li>
</ul>
Bonus Points
<ul>
<li>Marketplace or e-commerce experience</li>
<li>Publications, open-source work, or public writing on search and recommender systems.</li>
<li>MS or PhD in CS, Statistics, or a related field.</li>
</ul>
Salary Range
Canada: the pay range for this role is $180,000 to $247,500 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.
Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.
This job posting is for an existing vacancy.<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 ML/AI Scientist - Search

<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
Search is how retailers do their jobs on Faire. Wholesale queries and retailer expectations look different from consumer e-commerce and the right product depends on the store's category, price point, and aesthetic. When we get it wrong, it costs real money.
The Search algorithms team owns everything between the click on the search bar and the final ranker: typeahead and empty-state suggestions, query understanding, retrieval across five-plus independent sources, relevance modeling, and result-page surfaces like carousels and refinements. Within our scope, scientists own components outright: when you own query understanding here, you own the models, the roadmap, and the metrics.
You'll work across the full modern search stack: transformer-based embedding retrieval serving live traffic, LLMs powering query understanding and query rewriting, fine-tuned vision-language models scoring relevance, and graph-based retrieval — with generative retrieval and semantic IDs on the horizon.
What you'll do
<ul>
<li>Contribute to the next-generation Search engine, integrating LLMs, query understanding, dense vector retrieval, deep personalization embeddings, multi-stage ranking, and reinforcement learning to serve personalized product feeds with &lt;100ms latency.</li>
<li>Own one or more search components end to end: problem framing, modeling, production code, experiment design, and the call on what to build next.</li>
<li>Ship to live traffic and let A/B tests, not opinions, settle what works.</li>
<li>Raise the team's bar through design reviews, pairing, and honest post-mortems</li>
</ul>
You're a great fit if you have
<ul>
<li>3+ years building production ML systems, with meaningful time in search, recommendations, or another retrieval-and-relevance domain.</li>
<li>Shipped models that served real traffic, and owned the experiments that proved (or disproved) their value.</li>
<li>Depth somewhere in the modern retrieval stack — dual encoders and ANN serving, LLM-based query understanding, learning-to-rank fundamentals — and the ability to pick up the rest. </li>
<li>Strong Python and the engineering chops to take your own models to production.</li>
<li>Clear communication with scientists, engineers, and PMs: you make a crisp case for your ideas and update quickly when someone has a better one.</li>
<li>Excellent product judgment to connect customer and business context to technical decisions</li>
</ul>
Bonus Points
<ul>
<li>Marketplace or e-commerce experience</li>
<li>Publications, open-source work, or public writing on search and recommender systems.</li>
<li>MS or PhD in CS, Statistics, or a related field.</li>
</ul>
Salary Range
US: 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>

<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 member of the Retailer Growth Data team focusing on the paid marketing and top-of-funnel acquisition channels, you will develop AI/ML systems that help activate new retailers and increase their engagement. There are a wide range of ML opportunities in paid marketing optimization, from bidding optimization, search keywords intelligence, smart audience targeting to incrementality and efficiency estimation. With AI fast-growing and changing every aspect of the world, AEO (Answer Engine Optimization) is the new chapter of growth that yet needs to be figured out, where there is a huge opportunity to leverage ML and LLM to create programmatic content at scale, build reinforcement learning systems for fast feedback loop, and optimize landing experience to improve conversion.  
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>Drive data science vision, strategy, and execution within Retailer Growth, using AI/ML solutions to activate and engage more retailers on the platform</li>
<li>Work with cross-functional stakeholders to develop end-to-end product solutions</li>
<li>Extract deep behavioral insights using AI to automate AEO content creation and personalize the user landing experience.</li>
<li>Optimize marketing capital allocation through sophisticated targeting and bidding optimization strategies.</li>
<li>Implement rigorous experimentation and causal inference frameworks to quantify the impact of growth levers.</li>
<li>Engineer scalable solutions for complex challenges inherent to two-sided marketplace dynamics.</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)</li>
<li>Experience with relevant technical methods (LTV modeling, NLP, LLMs, causal ML, bidding optimization)</li>
<li>Strong programming skills</li>
<li>An excitement and willingness to learn new tools and techniques</li>
<li>The ability to design and implement ML solutions without 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 in paid marketing, and/or growth team focusing on SEO and AEO optimization</li>
<li>Previous experience in LLMs and programmatic content generation</li>
</ul>
Salary Range
Canada: the pay range for this role is $180,000 to $247,500 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.
Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.
This job posting is for an existing vacancy.<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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