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AI Two-Sided Market Trust Developer

Eli Sato

Full-time · Job · Los_Angeles

About the role

Trust in a two-sided marketplace is hard to measure and easy to destroy. A buyer who gets scammed does not just churn — they leave reviews, tell friends, and the trust damage compounds. A seller who gets falsely flagged does not just appeal — they post publicly and the resulting PR incident costs more than the prevented fraud. Getting trust scoring right on both sides simultaneously is the central product challenge for any marketplace. Our marketplace serves 2.8 million active users across buyer and seller sides. The current trust system scores each side independently. What is missing is a joint model: one that understands the trust dynamics of specific buyer-seller interaction patterns, that learns from resolved dispute outcomes rather than just reported incidents, and that handles the cold-start problem for new participants who have no history. You will own the joint trust model architecture — designing the interaction-level features, building the dispute outcome feedback loop, and developing the cold-start trust signals that combine profile completeness, payment method risk, and behavioral patterns from the first few sessions.

Responsibilities

  • Design joint trust model capturing buyer-seller interaction risk patterns
  • Build dispute outcome feedback pipeline for closed-loop trust signal improvement
  • Develop cold-start trust scoring for new participants with no transaction history
  • Implement trust score monitoring and drift detection across user cohorts
  • Design appeals workflow that uses model uncertainty to route borderline cases
  • Collaborate with trust and safety operations team on investigation workflows

Requirements

  • 6+ years in ML engineering with marketplace trust, fraud, or risk domain experience
  • Experience building two-sided market models or interaction-level risk systems
  • Strong Python, PyTorch, and Spark skills for large-scale user event processing
  • Deep statistical knowledge for trust signal design and evaluation
  • Track record shipping ML systems with direct business impact in marketplace settings

Benefits

  • Fully remote — US time zones preferred
  • Top-of-market compensation
  • Health, dental, and vision
  • Significant equity package
  • $6,000 annual professional development budget

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch spark sql statistics

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch spark sql statistics aws

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