Staff Machine Learning Engineer, Programmatic Ads

Pinterest Pinterest · Consumer · San Francisco, CA · Monetization

Staff Machine Learning Engineer for Programmatic Ads at Pinterest, focusing on developing core bidding and ranking systems. The role involves designing and implementing algorithms for real-time bidding, ad scoring, inventory selection, and yield optimization, owning end-to-end ML systems, and integrating new signals. The position emphasizes using AI to accelerate analysis and experimentation, with a requirement for experience in large-scale production ML systems in ads, search, or recommendations.

What you'd actually do

  1. Design and implement algorithms for real-time bidding, ad scoring/ranking, inventory selection, and yield optimization across multiple exchanges.
  2. Own end-to-end ML systems: problem framing, metrics, data/feature design, model training, evaluation, and online experimentation.
  3. Introduce and productionize new exchange and supply signals (e.g., quality, conversions, identity, fraud, content understanding) to unlock incremental advertiser value.
  4. Partner closely with Ads Ranking & Bidding, Measurement, and Programmatic Engineering to integrate new models and objectives into the ads stack.
  5. Use AI to accelerate analysis, experimentation, and iteration (e.g., exploring model variants, automating path from learnings to launch) while applying strong judgment and vision.

Skills

Required

  • Industry experience building and shipping large-scale production ML systems in ads, search, recommendations, or related domains.
  • Deep experience with control/optimization algorithms for bidding, pacing, allocation, or similar marketplace problems.
  • Strength in probabilistic modeling and measurement (e.g., quality/fraud signals, deep-learning engagement prediction) and making principled trade-offs between coverage, accuracy, and impact.
  • Proven Staff-level technical leadership as an IC: driving technical direction and cross-team alignment without formal people management.
  • Demonstrated ability to use AI to improve speed and quality of your workflow, with a strong track record of validating and stress-testing AI-assisted outputs.
  • Experience with Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring.
  • Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration.

Nice to have

  • Degree in Computer Science, Statistics, or a related field.

What the JD emphasized

  • building and shipping large-scale production ML systems in ads, search, recommendations, or related domains
  • Deep experience with control/optimization algorithms for bidding, pacing, allocation, or similar marketplace problems
  • Proven Staff-level technical leadership as an IC
  • Demonstrated ability to use AI to improve speed and quality of your workflow, with a strong track record of validating and stress-testing AI-assisted outputs

Other signals

  • building and shipping large-scale production ML systems
  • real-time bidding, ad scoring/ranking, inventory selection, and yield optimization
  • end-to-end ML systems: problem framing, metrics, data/feature design, model training, evaluation, and online experimentation
  • Use AI to accelerate analysis, experimentation, and iteration