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Machine Learning Engineer, Programmatic Ads

Job in Palo Alto, Santa Clara County, California, 94306, USA
Listing for: Segment (Twilio)
Full Time position
Listed on 2026-07-26
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 222716 - 389753 USD Yearly USD 222716.00 389753.00 YEAR
Job Description & How to Apply Below
Position: Staff Machine Learning Engineer, Programmatic Ads

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 building a new Programmatic Ads ML team to bring in exchange-sourced ads demand and supply. We’re looking for a Staff ML engineer to develop core bidding and ranking systems that help us optimally buy and sell inventory across exchanges, driving strong ROI for advertisers and growing a critical revenue stream for Pinterest.

What you’ll do:
  • Design and implement algorithms for real-time bidding, ad scoring/ranking, inventory selection, and yield optimization across multiple exchanges.
  • Own end-to-end ML systems: problem framing, metrics, data/feature design, model training, evaluation, and online experimentation.
  • Introduce and product ionize new exchange and supply signals (e.g., quality, conversions, identity, fraud, content understanding) to unlock incremental advertiser value.
  • Partner closely with Ads Ranking & Bidding, Measurement, and Programmatic Engineering to integrate new models and objectives into the ads stack.
  • 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.
What we’re looking for:
  • 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.
  • Degree in Computer Science, Statistics, or a related field.
  • 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 ourPinFlex 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-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…

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