Staff Machine Learning Engineer, Ads Conversion Core Modeling
Pinterest · San Francisco, United States +2 · 2mo ago
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.
We are looking for a Staff Machine Learning Engineer to lead the technical vision for our Ads Conversion Core Modeling team, building the state-of-the-art systems that power our global marketplace.
What you’ll do:
- Lead the technical direction and development of state-of-the-art 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 better understand intention and infer interests from online activity.
- Use AI to accelerate analysis and iteration, while applying judgment and verification to ensure correctness and quality.
- Automate repeatable tasks such as documentation, reporting, and QA checks to speed up the development lifecycle.
- Coach and mentor engineers while collaborating with product and sales to design new ad products.
What we’re looking for:
- 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 your day-to-day workflow 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.
- High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final deliverables.
- Strong mathematical foundation and experience with statistical methods and A/B testing.
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 1-2 times per month and therefore needs to be in a commutable distance from one of the following offices: San Francisco, Palo Alto, Seattle.
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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: