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AI Graph-Based Product Recommendation Engineer

Isaac Singh

Full-time · Job · New_York

About the role

PyTorch Geometric, Spark for graph construction at scale, and a knowledge graph spanning millions of product relationships are the core of what you'll build on. If graph neural networks for recommendation are your thing, this is the role. You will design and train GNN-based recommendation models that use our existing product knowledge graph to surface relevant items, moving beyond the collaborative filtering baseline we currently rely on. We publish internally and encourage you to bring in techniques from recent graph learning research rather than reinventing them. This is interesting work because the knowledge graph already exists at scale, so you get to focus entirely on modeling quality instead of building graph infrastructure from zero.

Responsibilities

  • Design and train GNN-based recommendation models
  • Benchmark against the existing collaborative filtering baseline
  • Adapt recent graph learning research to production constraints
  • Partner with the knowledge graph team on schema needs
  • Present modeling results at internal research reviews

Requirements

  • 5+ years building recommendation or graph ML systems
  • Experience with PyTorch and Spark
  • Strong understanding of graph neural network architectures
  • Comfortable working with large-scale knowledge graphs

Benefits

  • Fully remote
  • Research compute budget
  • Health insurance
  • Conference attendance support

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Categories

AI & Machine Learning Engineers data science & analytics

Skills

python pytorch spark sql

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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

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