New York City, NY; San Francisco, CA
Open 4 months, first seen by us 139 days agoSalary 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.Read the full posting
Faire is building the future of wholesale, connecting independent retailers with the brands that will define their stores.
As a Senior Applied AI/ML Scientist on the Compass team, you will be the science and technical lead for this product — driving agent quality through data, evaluation, and modeling, while shipping product features end-to-end with high velocity.
Set the data-grounded direction for agent design and context strategy
Ship retailer-assistant features end-to-end across Python app, data and frontend
Define offline eval suites and LLM-as-judge quality metrics
Turn ambiguous product bets into sequenced, de-risked plans
Partner with engineers on architecture and serving tradeoffs
Faire is building the future of wholesale, connecting independent retailers with the brands that will define their stores. At the heart of this mission is Compass — Faire’s user facing AI bet within the Discovery Pillar — building an always-present, context-aware retailer assistant along the enagement journey. Compass helps retailers make smarter buying decisions by combining Faire’s rich proprietary data with agentic AI and web search, and is increasingly able to take action on retailers’ behalf.
As a Senior Applied AI/ML Scientist on the Compass team, you will be the science and technical lead for this product — driving agent quality through data, evaluation, and modeling, while shipping product features end-to-end with high velocity. This is a deeply hands-on individual contributor role: no direct reports, keyboard first. You will set the data-grounded direction for how the assistant works, while also being a full-stack (AI, ML, backend) builder who turns ideas into shipped product fast.
Own the science and technical north star for Compass’s agentic products
Ship retailer-assistant features end-to-end — across the FLARE Python app, data plumbing, tool wrappers, and the frontend surfaces
define how the team knows an agent is good, including offline eval suites, LLM-as-judge metrics
Translate ambiguous product bets into sequenced, de-risked tactical plans
Partner closely with engineers on architecture and serving tradeoffs
Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores.
In the employer’s words · Read in context
Open 4 monthsWe first saw this posting 139 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Day 139
Up longer than most. Similar jobs usually come down between day 4 and day 77.
At Faire, jobs usually come down by about day 70.
From 51 similar postings that came down, and 8 of Faire’s. Coming down is not always a hire.
24 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Own the science and technical north star for Compass’s agentic products — the retailer assistant today and whatever comes next: how to leverage Faire’s proprietary data, agent + tool + context strategy (preload vs. tool-calling vs. hybrid), and how to measure and raise agent quality as systems gain the ability to act. - Ship retailer-assistant features end-to-end — across the FLARE Python app, data plumbing, tool wrappers, and the frontend surfaces where the assistant appears, using AI-native workflows to multiply your output. - Translate ambiguous product bets into sequenced, de-risked tactical plans — what to build now, what to defer, and which bets carry the highest impact × probability-of-success.
- Hands-on experience with the OpenAI Agents SDK or similar agentic frameworks in production. - Familiarity with preload-over-RAG context strategies, Snowflake-backed grounding, or hybrid approaches. - Prior 0→1 / early-stage product experience — has built something meaningful from scratch.
Complete your application on boards.greenhouse.io. The employer’s form will show what is required.
Already applied? Track this application
New AI Engineer postings at the employers we follow are up 134% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under AI Engineer, by the work the posting describes.
AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.
Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.
An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.
About Faire
Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive.
We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.
About the role
Faire is building the future of wholesale, connecting independent retailers with the brands that will define their stores. At the heart of this mission is Compass — Faire’s user facing AI bet within the Discovery Pillar — building an always-present, context-aware retailer assistant along the enagement journey. Compass helps retailers make smarter buying decisions by combining Faire’s rich proprietary data with agentic AI and web search, and is increasingly able to take action on retailers’ behalf.
As a Senior Applied AI/ML Scientist on the Compass team, you will be the science and technical lead for this product — driving agent quality through data, evaluation, and modeling, while shipping product features end-to-end with high velocity. This is a deeply hands-on individual contributor role: no direct reports, keyboard first. You will set the data-grounded direction for how the assistant works, while also being a full-stack (AI, ML, backend) builder who turns ideas into shipped product fast.
You will work at the frontier of agentic AI, blending applied science rigor (eval-driven development, experimentation, data strategy) with cross-stack engineering range to build the retailer assistant of the future. This is a rare opportunity to shape a product from near-zero — where your judgment, speed, and instincts will define the outcomes.
What you’ll do
You’re a great fit if you have…
Bonus points for…
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.
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
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 (https://bit.ly/faire-form)
Privacy
For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire’s Privacy Notice (https://www.faire.com/privacy)
Selected passages from the saved posting. Check the full description for conditions and exceptions.
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.
New York City, NY; San Francisco, CA
What you’ll do - Own the science and technical north star for Compass’s agentic products — the retailer assistant today and whatever comes next: how to leverage Faire’s proprietary data, agent + tool + context strategy (preload vs. tool-calling vs. hybrid), and how to measure and raise agent quality as systems gain the ability to act. - Ship retailer-assistant features end-to-end — across the FLARE Python app, data plumbing, tool wrappers, and the frontend surfaces where the assistant appears, using AI-native workflows to multiply your output.
- Hands-on experience with the OpenAI Agents SDK or similar agentic frameworks in production. - Familiarity with preload-over-RAG context strategies, Snowflake-backed grounding, or hybrid approaches. - Prior 0→1 / early-stage product experience — has built something meaningful from scratch.
More relevant text appears in the full description.
No clear work-authorization passage found. Eligibility is unconfirmed.