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AI Real-time Interest Graph Builder

Aaliyah Okafor

Full-time · Job · New_York

About the role

Recommendation systems that rely on static user profiles are always serving yesterday's interests. A user who spent the last hour reading about machine learning infrastructure doesn't want to see the celebrity gossip article that ranked highest in their long-term interest model. Real-time interest graph construction — building a continuously updated representation of what each user cares about right now, not six months ago — is the capability that closes this gap. Our personalization platform serves 22 major media and e-commerce clients with a combined 180 million monthly active users. The existing interest modeling infrastructure is batch-based, updating user profiles nightly. We've built the streaming foundation; we need someone who can build the intelligence layer on top of it: graph-based interest representation that captures semantic relationships between topics, recency-weighted signal processing, and the real-time serving infrastructure that delivers personalized recommendations within 20 milliseconds of a page load. This is a principal-level IC role shaping the next generation of our personalization architecture. You'll own the technical direction for real-time interest modeling, collaborate with ML platform engineers on the serving infrastructure, and present performance results to C-level stakeholders at client companies who are evaluating the business impact on engagement and revenue.

Responsibilities

  • Design real-time interest graph architecture representing semantic topic relationships with recency weighting
  • Build streaming signal processors updating user interest states from click, dwell, and interaction events
  • Implement sub-20ms interest retrieval serving infrastructure integrated with recommendation endpoints
  • Develop interest decay models distinguishing transient session interests from durable long-term preferences
  • Create evaluation framework measuring real-time personalization lift against batch baseline
  • Present architecture decisions and business impact results to client C-level stakeholders

Requirements

  • 8+ years in personalization, recommendation systems, or real-time ML infrastructure
  • Deep expertise in graph-based user modeling and streaming ML systems
  • Strong Python and Spark skills with low-latency serving system design experience
  • Experience shipping recommendation systems serving 100M+ users
  • Track record influencing platform architecture direction and presenting to executive stakeholders

Benefits

  • Fully remote with flexible schedule
  • Top-of-market total compensation package
  • Comprehensive health benefits
  • $6,000 annual professional development budget
  • Significant equity participation

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Categories

AI & Machine Learning Engineers AI Business, Marketing & Strategy

Skills

python pytorch spark aws fastapi

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$200k+ / year

AI Expertise

AI & Machine Learning Engineers AI Business, Marketing & Strategy

Skills

python pytorch spark aws fastapi sql

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