Staff ML Engineer: Ads AI Leader (Hybrid, Equity)

Pinterest; San Francisco (CA); On-site; USD 222,716 - 389,753; Full time

Job summary

Pinterest is seeking a Staff Machine Learning Engineer to lead the technical vision for our Ads Conversion Core Modeling team, building state-of-the-art systems for a global marketplace.

You will design large-scale DNN models to improve user action prediction with low latency, mine signals to infer interests, and accelerate analysis using AI while ensuring quality. This US-based role requires onsite collaboration in SF, Palo Alto, or Seattle.

Qualifications

• Bachelor's degree in Computer Science, Statistics, or a related field.
• 6+ years of industry experience building production ML systems at scale (Search, Recommendations, or Ranking).
• 2+ years of experience leading technical projects or teams.
• Demonstrated ability to use AI to improve speed and quality in day-to-day workflow.
• Experience with AI coding assistants for development, debugging, testing, and refactoring.
• Familiarity with LLM-powered productivity tools for documentation search and analysis.
• Strong integrity, ownership and accountability for final deliverables.
• Solid foundation in statistics and A/B testing.

Responsibilities

• Lead the technical direction and development of applied ML projects for ads conversion.
• Design and build large-scale DNN models to improve user action prediction with low latency.
• Mine text, visual, and user signals to infer interests from online activity.
• Use AI to accelerate analysis and iteration while ensuring quality and verification.
• Automate tasks such as documentation, reporting, and QA checks.
• Coach and mentor engineers, collaborating with product and sales on ad products.

Skills

Production ML

Leadership

AI tools

LLM productivity tools

Statistical methods

Education

Bachelor's degree in Computer Science or Statistics

Tools

Cursor

Copilot

Codex

Job description

Pinterest is seeking a Staff Machine Learning Engineer to lead the technical vision for our Ads Conversion Core Modeling team, building state-of-the-art systems for a global marketplace.

You will design large-scale DNN models to improve user action prediction with low latency, mine signals to infer interests, and accelerate analysis using AI while ensuring quality. This US-based role requires onsite collaboration in SF, Palo Alto, or Seattle.