San Francisco, United States
Staff Machine Learning Engineer - Ads Bidding & Pacing
Pinterest · San Francisco · United States
Posted: 9/29/2026 · Last checked: 10/12/2026
Job description
Quoted in full from Pinterest's job posting. Gavroche does not edit it.
About Pinterest:
Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.
At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.
Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
Pinterest is one of the fastest growing online ad platforms, and our success depends on building a suite of bid strategies that help advertisers achieve their goals within the Pinterest marketplace.
We support both automatic bidding (maximizes the number of clicks, conversions and GMV) as well as target average bidding (CPA or ROAS targets) for Pinterest ads. We’re looking for an ML engineer with experience in ads delivery, machine learning, bid landscapes, and automatic bidding / ads pacing to develop new data-driven techniques to drive ads delivery performance and maximum ROI for advertisers, growing Pinterest’s revenue stream.
What you’ll do:
- Design target ROAS and automatic bidding & pacing algorithms for ads.
- Explore bid landscapes to maximize revenue and advertiser value.
- Work with product and sales teams to design and implement bidding strategies for new ad products.
- A/B Experiment with bidding algorithm improvement ideas.
- Collaborate with other teams to identify bidding and budgeting opportunities and capitalize on them.
What we’re looking for:
- Bachelor's degree in Computer Science, Statistics, a related field, or equivalent experience.
- 6+ years of industry experience in ads delivery, automatic bidding / pacing, target ROAS bidding, ads marketplace / utility, or machine learning.
- 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.
- Degree in Computer Science, Statistics, or a related field.
- Direct experience specifically with bidding or pacing is a big plus.
- Bachelor's degree in computer science, statistics, engineering, or
- 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.
Relocation Statement:
- This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
In-Office Requirement Statement:.
- We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
- This role will need to be in the office for in-person collaboration 3 times per quarter and therefore needs to be in a commutable distance from one of the following offices: San Francisco, Palo Alto, Seattle.
#LI-HYRBID
#LI-SM4
At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
Our Commitment to Inclusion:
Similar roles in San Francisco
- MACHINE LEARNING ENGINEER - GENERAL · MakerMaker, San Francisco
- AI Engineer · Max AI, Inc., San Francisco
- Research Scientist - Dynamical Systems & AI · Becoming, San Francisco
- PhD University Grad Machine Learning Engineer - USA · Pinterest, San Francisco
- Principal Machine Learning Engineer - TEAM · DoorDash USA, San Francisco
- Machine Learning Engineer Intern · ATOMS Careers page, San Francisco
200 open roles like this one; at most three per employer shown.
What data scientist adverts in San Francisco state
Middle half: 187,125 – 268,462 USD a year; median 236,250 USD.
From 54 adverts by 26 employers that state a salary, annualised.
How data scientist roles in the United States are worked
8% fully remote · 2% hybrid · 90% do not say
Of 91 adverts. An advert that does not state a work mode is counted as not saying, not as on-site.
New openings in San Francisco, by week
- 7/20/2026 99
- 7/27/2026 110
- 8/3/2026 130
- 8/10/2026 175
- 8/17/2026 172
- 8/24/2026 170
- 8/31/2026 250
- 9/7/2026 240
- 9/14/2026 285
- 9/21/2026 343
- 9/28/2026 340
- 10/5/2026 316
- 10/12/2026 33
2,663 openings over 12 weeks, by the week they were published.
Other roles at Pinterest
- Director - Machine Learning Engineering - Ads Measurement · San Francisco
- Sr. Staff Software Engineer - Product ML Infrastructure · Palo Alto
- Staff Software Engineer - Ads & Core Serving Platform · Palo Alto
- Machine Learning Engineer - EPD Ads · San Francisco
- Master's University Grad Machine Learning Engineer 2027 - USA · San Francisco
- Principal Machine Learning Engineer - Ads Delivery · San Francisco
58 open, including roles outside the United States.