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Staff Applied AI/ML Scientist

Faire
Location
San Francisco, CA
Posted
26 days ago
Department
Algorithms & Data
Salary
$246,500 to $339,000
What they actually want (must-haves)
  • 5+ years of industry experience using machine learning to solve real-world problems
  • Experience with relevant business problems (e-commerce, marketplaces, growth, personalization, incentives, or trust and quality)
  • Experience with relevant technical methods (causal inference, predictive/LTV modeling, recommendations, information extraction, entity resolution, and/or deep learning and LLMs)
  • Strong programming skills
  • Experience as a tech lead, mentoring other scientists or machine learning engineers
  • Strong communication skills and the ability to work in a highly cross-functional team
Nice to have
  • Master's or PhD in Computer Science, Statistics, or related STEM fields
  • Experience as a tech lead manager or people manager of applied ML / data science teams
  • Previous experience in marketplace growth, incentive optimization, or trust and quality for a two-sided platform
  • Previous experience with deep learning or language models
What the job really is

As a Staff Applied AI/ML Scientist at Faire, you will lead the development of machine learning models that enhance the experience of independent retailers in a two-sided marketplace. Your responsibilities include driving data science strategies, optimizing marketing efforts, and mentoring other scientists while working with diverse data types to solve complex problems related to personalization and marketplace quality.

Benefits
  • Competitive pay
  • Equity
  • Comprehensive benefits designed to support your life inside and outside of work
  • Hybrid work model with flexibility to work remotely up to 4 weeks per year
Things to weigh
  • No specific technologies or tools mentioned, which may indicate a need for adaptability
  • The role involves leading and mentoring, which may require strong interpersonal skills and experience in team dynamics
Job score3.8/5
Benefits2/5
Freshness4/5
Career value4/5
Role clarity4/5
Pay transparency5/5

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