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AI Discovery Feed Algorithm Engineer

Eli Sato

Full-time · Job · Los_Angeles

About the role

The discovery feed is the single most important surface in our marketplace — it drives 48% of all buyer-seller connections and directly influences $340M in annual GMV. The feed algorithm decides what 2.8 million users see when they open the app, and small improvements translate into measurable revenue impact. A 1% lift in feed engagement last quarter generated $4.2M in incremental GMV. We're hiring a senior engineer to own the ranking model and its supporting infrastructure. The current system uses a two-tower architecture for candidate retrieval and a gradient-boosted ranker for final ordering. Your job is to evolve both stages: exploring transformer-based architectures for retrieval, adding real-time behavioral signals to ranking, and building the experimentation framework that lets us test changes safely on a marketplace where both sides of the transaction are affected. You'll work with a product manager, a data scientist, and two backend engineers who handle serving infrastructure. This is a high-leverage IC role where your technical choices have direct business impact measurable in dollars per week.

Responsibilities

  • Own the discovery feed ranking model end-to-end: training, evaluation, and serving
  • Evolve candidate retrieval from two-tower to more expressive architectures
  • Incorporate real-time behavioral signals into ranking features
  • Build experimentation frameworks for safe A/B testing on a two-sided marketplace
  • Analyze feed performance metrics and identify optimization opportunities
  • Partner with product to translate business goals into model objectives

Requirements

  • 7+ years in recommendation systems or ranking at scale
  • Deep expertise in learning-to-rank, retrieval models, and online experimentation
  • Production experience serving models at millions of daily active users
  • Strong Python, PyTorch, and SQL skills
  • Track record of measurable business impact from model improvements

Benefits

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

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch spark sql aws

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$200k+ / year

AI Expertise

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch spark sql aws statistics

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