Staff Software Engineer, Measurement Interfaces

🚀 Staff Machine Learning Engineer, Ads Retrieval
📍 Location: San Francisco | Palo Alto | Seattle
🕒 Job Type: Regular | Full-time

About Pinterest

Millions of people use Pinterest daily to discover new ideas and inspiration. Our mission is to help them create a life they love by connecting them with relevant content, including Shopping Ads. At Pinterest, you’ll have the opportunity to work on groundbreaking innovations while making a real impact on our users and advertisers.

Role Overview

Join our Ads Retrieval Team and play a key role in shaping the future of our global Shopping Ads platform. As a Staff Machine Learning Engineer, you’ll lead the development of cutting-edge retrieval models and scalable infrastructure. You’ll work on areas like Generative Retrieval, User Sequence Modeling, Learning to Rank, and large-scale Approximate Nearest Neighbor (ANN) techniques, all while managing a 5B+ shopping ads index.

What You’ll Do

✅ Develop Next-Gen Retrieval Models

• Design and implement advanced retrieval architectures, improving ad relevance and ranking.
• Pioneer Generative Retrieval, User Sequence Modeling, and Learning-to-Rank models to enhance discovery.

✅ Optimize Scalable Retrieval Infrastructure

• Build and refine high-performance retrieval systems for handling large-scale datasets.
• Implement efficient ANN algorithms, GPU-accelerated systems, and embedding quantization for fast and cost-effective retrieval.

✅ Advance Personalized Shopping Ads

• Leverage user sequence modeling to tailor shopping recommendations.
• Apply deep learning techniques to improve ad relevance and engagement.

✅ Collaborate Cross-Functionally

• Work with Product, Data Science, and Engineering teams to enhance ad performance.
• Drive innovation across the entire Shopping Ads ecosystem.

What We’re Looking For

🎓 Education & Experience

• MS or PhD in Computer Science, Statistics, or a related field.
• 6+ years of experience in building large-scale recommendation or search systems.

💡 Technical Expertise

• Strong foundation in Machine Learning & Information Retrieval.
• Expertise in retrieval algorithms (Generative Retrieval, User Sequence Modeling, Learning-to-Rank, ANN techniques).
• Deep knowledge of deep learning optimization for retrieval tasks.
• Experience scaling GPU-based systems for high-throughput retrieval.
• Proficiency in large-scale retrieval efficiency techniques (ANN, embedding quantization, etc.).

🤝 Collaboration & Leadership

• Ability to lead technical projects and mentor junior engineers.
• Excellent communication skills to drive consensus across teams.

Bonus Points

✨ Hands-on experience with Shopping Ads and computational advertising.
✨ Proven track record in optimizing retrieval infrastructure at scale.
✨ Familiarity with Large Language Models (LLMs) and token-based retrieval.

Work Location & Flexibility

📍 Hybrid Role – In-office collaboration required once per month at one of our offices: San Francisco, Palo Alto, or Seattle.
📦 Relocation assistance is not available for this role.

Compensation & Benefits

💰 Salary Range: $208,145—$364,254 USD (based on location & experience).
📈 Equity options available.
🌍 Inclusive & diverse workplace with strong growth opportunities.

Join Us!

At Pinterest, we celebrate diversity and innovation. If you’re excited about working on cutting-edge Machine Learning for Ads Retrieval, we’d love to hear from you! Apply now and help shape the future of Pinterest Shopping Ads. 🚀

📌 Apply Today!