Staff Machine Learning Engineer, Ads Conversion Core Modeling

Pinterest

Confirmed live yesterday Trusted
Hybrid

Quick summary

Work type
Hybrid
Location
San Francisco, CAPalo Alto, CASeattle, WA
Salary
$222,716–$389,753 / yr
Posted
11 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $235k
This role $306k
$160k $414k
below market most similar roles pay here above market

This role pays more than 92% of similar roles. Most pay $214,000–$255,062 — the blue band above. At the midpoint, this role pays about $306k versus about $235k for comparable roles.

Based on 240 similar postings.

Employer

About Pinterest

Pinterest is a visual discovery and inspiration platform where people find ideas for home, style, recipes, and more. It serves hundreds of millions of users worldwide through its image and video pinboard product.

Pinterest currently has 76 open roles on FindRole.

Listed pay typically runs $177,185–$339,078 across 70 roles with salary data.

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View all roles at Pinterest

At a glance

TL;DR · Staff Machine Learning Engineer, Ads Conversion Core Modeling

The Staff Machine Learning Engineer joins the Ads Conversion Core Modeling team to lead the technical vision for state-of-the-art applied machine learning projects. The role involves designing and building large-scale deep neural network models to improve user action prediction with low latency. Key responsibilities include mining text, visual, and user signals to infer interests from online activity, automating repeatable tasks like QA checks, and mentoring other engineers. The position requires a strong mathematical foundation in statistical methods and A/B testing. Candidates must demonstrate experience with production ML systems for search, recommendations, or ranking. Technical requirements include using AI coding assistants like Cursor, Copilot, or Codex, alongside LLM-powered productivity tools for SQL data exploration and experiment analysis to solve complex ads conversion problems.

What does a Machine Learning Engineer earn in California?

Median $235750 from 200 postings across 34 companies.

See salary data

What you'll do

  • 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 understand intent and infer interests from online activity.
  • Use AI tools to accelerate analysis, iteration, and the overall development lifecycle.
  • Automate repeatable tasks such as documentation, reporting, and QA checks.
  • Coach and mentor engineers while collaborating with product and sales teams to design new ad products.

What we're looking for

  • Bachelor's degree in Computer Science, Statistics, or a related field.
  • Minimum 6 years of industry experience building production ML systems at scale for Search, Recommendations, or Ranking.
  • Minimum 2 years of experience leading technical projects or teams.
  • Demonstrated ability to use AI to improve speed and quality in day-to-day workflows for relevant 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.
  • Strong mathematical foundation and experience with statistical methods and A/B testing.
  • Must be a US based applicant and live within a commutable distance of San Francisco, Palo Alto, or Seattle.

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