bluedoor data·Job Postings API·bluedoor.sh ↗

HomeCompaniesFaireSenior Applied AI/ML Scientist - Search Ads

Senior Applied AI/ML Scientist - Search Ads

Faire · San Francisco, CA · Hybrid · Deleted · $196,000–$269,500 / year · Greenhouse

Job facts

FieldValue
CompanyFaire
TitleSenior Applied AI/ML Scientist - Search Ads
Normalized title-
Department / teamAlgorithms & Data
LocationSan Francisco, CA, United States
Work modelHybrid / Hybrid
Employment typeRegular
Salary$196,000–$269,500 / year
Statusdeleted
ATS providerGreenhouse
Posted / first seen2026-01-30 / 2026-05-29
Changed / last seen2026-06-06 / 2026-06-03

Related slices

PageWhat it containsOpen
Company jobsActive postings from Faire.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Greenhouse.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in San Francisco.Open
Department jobsActive postings in Algorithms & Data.Open
Work model jobsActive Hybrid postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyFaire
Source9237a19f-15f6-4b90-8eee-1a6065fe3cbc
ATS providerGreenhouse

Description

About Faire Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so businesses can grow and local communities can thrive. We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours. About this Role The Ads Data team is building the next generation of advertising products for the wholesale industry. As a key member of this team, you’ll help drive the ML algorithm strategy and system design behind one of the most critical levers for customer value and company growth—Search Ads. You’ll lead the advancement of real-time systems that decide which ads to show for a query, where to place them, and how to optimize for relevance, marketplace health, and advertiser outcomes. This role mirrors many of the technical expectations of Faire’s organic Search roles (modern NLP/LLMs, query understanding, real-time ranking), while operating in an ads environment with auctions, budgets, and pacing constraints. You’ll operate at the forefront of algorithms—combining large language models, natural language processing, query understanding, deep learning, and structured behavioral data to deliver highly relevant sponsored results for any given query. What You'll Do Own and evolve the Search Ads relevance stack—spanning query understanding, targeting, candidate generation, multi-stage ranking, and calibration—while meeting stringent latency and reliability goals. Design and productionize ML models that improve sponsored-result relevance and personalization, using a blend of unstructured signals (text/images where applicable), LLM-based representations, and structured marketplace features. Partner closely with engineering and product to connect relevance improvements to ads marketplace outcomes (e.g., conversion, long-term retailer experience, advertiser ROI), using rigorous offline evaluation and online experiments. As an early member of the Ads Data team, help define its roadmap and technical culture, leveraging deep product intuition to shape what ads at Faire should be—not just how they’re built. Work in a fast-paced, collaborative environment with team members who’ve shipped ML at top tech companies (e.g. Uber, Airbnb, Meta, Amazon, Pinterest). Qualifications 4+ years of experience building and shipping ML systems in production, with meaningful experience in search, recommendation, or ads ranking/retrieval. Hands-on experience with modern deep learning tooling (e.g., PyTorch) and familiarity with vector search / embedding-based retrieval concepts (e.g., Faiss, ScaNN, Pinecone). A strong track record of productionizing models that blend LLMs (e.g., BERT / GPT-class) with structured features to drive relevance and personalization. Product-focused mindset and a bias toward execution—moving quickly from research to measurable user and business impact. Strong communication skills and the ability to work with others in a closely collaborative team environment Great to Haves Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields Ability to quickly implement state of the art algorithms from an academic paper Salary Range San Francisco: 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. 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 Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly. 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. 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. Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work. Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success. 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)

Full job record

Job ID255f5aba96cee32d5b9fbd7cf1f0097ae14f9177
Org IDf3dbef89-a28b-4f4c-aa34-aca6468e524b
Source ID9237a19f-15f6-4b90-8eee-1a6065fe3cbc
Board ID9237a19f-15f6-4b90-8eee-1a6065fe3cbc
Providergreenhouse
Provider Job Key8399389002
TitleSenior Applied AI/ML Scientist - Search Ads
Normalized Title
Statusdeleted
Activeno
Location TextSan Francisco, CA
DepartmentAlgorithms & Data
Team
Employment TypeRegular
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionCA
CitySan Francisco
Salary RawSalary Range San Francisco: the pay range for this role is $196,000 to $269,500 per year
Salary Min196,000
Salary Max269,500
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://boards.greenhouse.io/faire/jobs/8399389002?gh_jid=8399389002
Apply URLhttps://boards.greenhouse.io/faire/jobs/8399389002?gh_jid=8399389002
First Seen At2026-05-29 22:59:53Z
Last Seen At2026-06-03 11:14:04Z
Last Checked At2026-06-06 07:34:01Z
Last Changed At2026-06-06 07:34:01Z
Inactive At2026-06-06 07:34:01Z
Source Posted At2026-01-30 22:39:52Z
Source Updated At2026-04-08 14:48:01Z
Raw Payload Uris3://bluework-jobs-prod-raw-590183727216/raw/provider=greenhouse/board=faire/date=2026-06-03/2026-06-03T11-14-03-797Z-d0eaeae8e79481ab7db25fe941d5277be3eb24960abbb776f4bfceb90bd2e696.json
Event Fields
{
  "content_hash": "8197fa0859c8deb62611fb810aeedde0fa7268962974259048a9f215270ea028",
  "source_hash": "25c0aa2b69efc957f8afebc6853c976d51081200431dd0caa9f540a28bba5a5d",
  "last_changed_at": "2026-06-06T07:34:01.081Z",
  "active_status": "deleted"
}
Parsed Structured
{
  "language": "en",
  "location": {
    "raw": "San Francisco, CA",
    "city": "San Francisco",
    "region": "CA",
    "country": "United States",
    "is_remote": false,
    "confidence": 0.9
  },
  "salary_max": 269500,
  "salary_min": 196000,
  "inferred_at": "2026-06-03T11:14:04.126Z",
  "launch_scope": {
    "reason": "english_us_canada",
    "included": true,
    "language": "en",
    "location": {
      "raw": "San Francisco, CA",
      "city": "San Francisco",
      "region": "CA",
      "country": "United States",
      "is_remote": false,
      "confidence": 0.9
    },
    "countries": [
      "United States",
      "Canada"
    ]
  },
  "remote_policy": "hybrid",
  "salary_period": "year",
  "workplace_type": "hybrid",
  "salary_currency": "USD"
}
Extensions
{}
Native Structured
{
  "title": "Senior Applied AI/ML Scientist - Search Ads",
  "offices": [
    {
      "id": 4000905002,
      "name": "Kitchener-Waterloo, ON",
      "location": "Waterloo, Ontario, Canada",
      "child_ids": [],
      "parent_id": 4049475002
    },
    {
      "id": 4000970002,
      "name": "San Francisco, CA",
      "location": "San Francisco, California, United States",
      "child_ids": [],
      "parent_id": 4049474002
    },
    {
      "id": 4037984002,
      "name": "Toronto, ON",
      "location": "Toronto, Ontario, Canada",
      "child_ids": [],
      "parent_id": 4049475002
    }
  ],
  "language": "en",
  "location": {
    "name": "San Francisco, CA"
  },
  "metadata": [
    {
      "id": 4008562002,
      "name": "Employment Type",
      "value": "Regular",
      "value_type": "single_select"
    }
  ],
  "updated_at": "2026-04-08T10:48:01-04:00",
  "departments": [
    {
      "id": 4002179002,
      "name": "Algorithms & Data",
      "child_ids": [],
      "parent_id": null
    }
  ],
  "company_name": "Faire",
  "requisition_id": 6245137002,
  "first_published": "2026-01-30T17:39:52-05:00",
  "application_deadline": null
}
Get this page with API

Rendered from the bluedoor Job Postings API. Reproduce it:

GET https://api.bluedoor.sh/job-postings/v1/jobs/255f5aba96cee32d5b9fbd7cf1f0097ae14f9177?include=descriptionJSON
GET https://api.bluedoor.sh/job-postings/v1/orgs/f3dbef89-a28b-4f4c-aa34-aca6468e524bJSON
GET https://api.bluedoor.sh/job-postings/v1/sources/9237a19f-15f6-4b90-8eee-1a6065fe3cbcJSON
GET https://api.bluedoor.sh/job-postings/v1/jobs/255f5aba96cee32d5b9fbd7cf1f0097ae14f9177/eventsJSON