Staff Machine Learning Engineer, Content Quality Signals

Pinterest

Remote
$189,308 - $389,753 usd py
Hybrid (1-2 days in-office per quarter)
Lead modeling strategy for content understanding
Design and ship production models
Own the full ml lifecycle
Pinterest is seeking a Staff Machine Learning Engineer for their Content Quality Signals team, focusing on building and deploying machine learning models that enhance content understanding across the platform. The role requires strong technical leadership and experience in various machine learning domains, including computer vision and NLP

Job Summary

  • The Content Understanding team builds machine learning models that “read” Pinterest content—images, text, and video—to produce high-quality semantic signals.
  • These signals power relevance and retrieval for Homefeed, Search, Related Pins, and Ads, and also support integrity use cases like spam and low-quality detection.
  • The role is ideal for a senior modeler who also enjoys developing, productionizing models and leading technical direction across teams.

Matching Summary

Match Score: 85

Pinterest is seeking a Staff Machine Learning Engineer for their Content Quality Signals team, focusing on building and deploying machine learning models that enhance content understanding across the platform. The role requires strong technical leadership and experience in various machine learning domains, including computer vision and NLP.

Salary

$189,308 - $389,753 USD

Skills & Requirements

Must-have

  • Lead modeling strategy for content understanding
  • Design and ship production models
  • Own the full ML lifecycle
  • Partner with infra/platform teams
  • Collaborate with signal-consuming teams
  • Provide technical leadership

Nice-to-have

  • Experience with AI coding assistants
  • Familiarity with LLM-powered productivity tools

Key Requirements

  • M.S/ PhD degree in Computer Science, Statistics or related field
  • Significant industry experience building software and ML pipelines/systems
  • Strong proficiency in Python and at least one ML stack
  • Proven experience training and deploying ML models to production
  • Deep hands-on experience in content understanding domains
  • Experience working with large-scale datasets and distributed compute
  • Strong applied skills in evaluation and experimentation
  • Demonstrated ability to influence across teams

Work Rights

Not specified

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