Staff Machine Learning Engineer, Ads Conversion Core Modeling

Pinterest•Palo Alto, CA

8d•$222,716 - $389,753•Hybrid

About The Position

Pinterest is hiring a Staff Machine Learning Engineer to lead the technical vision for its Ads Conversion Core Modeling team and build state-of-the-art machine learning systems for its global marketplace. The role focuses on applied machine learning for ads conversion, including large-scale deep neural network models that improve low-latency prediction of user actions and the use of text, visual, and user signals to understand intent and infer interests from online activity. The engineer will use AI to accelerate analysis and iteration, while applying judgment and verification to ensure correctness and quality. The role also involves automating repeatable work such as documentation, reporting, and quality checks; mentoring engineers; and collaborating with product and sales teams to design new ad products. The position requires in-person collaboration at an office 1–2 times per month. The employee must live within commuting distance of the San Francisco, Palo Alto, or Seattle offices. The position is not eligible for relocation assistance. The listed US base salary range is $222,716–$389,753, and the position is also eligible for equity.

Requirements

Bachelor’s degree in Computer Science, Statistics, or a related field.
At least 6 years of industry experience building production machine learning systems at scale in Search, Recommendations, or Ranking.
At least 2 years of experience leading technical projects or teams.
Demonstrated ability to use AI to improve the speed and quality of day-to-day work for relevant outputs.
Experience using 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.
High integrity and ownership, including protecting sensitive data, avoiding over-reliance on AI, and remaining accountable for final deliverables.
Strong mathematical foundation and experience with statistical methods and A/B testing.
Must be within commuting distance of the San Francisco, Palo Alto, or Seattle offices for in-person collaboration 1–2 times per month.

Responsibilities

Lead the technical direction and development of state-of-the-art applied machine learning projects for ads conversion.
Design and build large-scale deep neural network models to improve low-latency user action prediction.
Mine text, visual, and user signals to understand intent and infer interests from online activity.
Use AI to accelerate analysis and iteration, applying judgment and verification to ensure correctness and quality.
Automate repeatable tasks such as documentation, reporting, and quality checks to speed up development.
Coach and mentor engineers.
Collaborate with product and sales teams to design new ad products.