Sr. Machine Learning Engineer, Responsible AI– Applied Research Science

About the role

Pinterest is on a mission to bring everyone the inspiration to create a life they love. The Responsible AI team is part of the Advanced Technologies Group (ATG), which works on advanced machine learning technology across multiple use cases including recommendations, ranking, content understanding, and more. The team focuses on having a direct impact on business metrics through its work on fairness, ethics, and broader societal considerations.

What You'll Do

• Design and drive projects in the responsible AI frontier to identify, avoid, and mitigate bias across a wide range of ML applications at Pinterest.
• Collaborate with other engineering teams (trust and safety, ML Platform, Content Understanding, Search, Homefeed) to leverage their platforms and signals and work with them to collaborate on the adoption and evaluation of Responsible AI practices and ML Fairness tooling across Pinterest.
• Mentor junior engineers on the Responsible AI team and across the company on the R-AI space.
• Work with the team and senior leaders at the company to define and drive technical strategy in this area.

What We're Looking For

• Extensive, real-world experience applying advanced ML methods to production systems, with a strong track record in responsible technology - spanning fairness, ethics, and broader societal considerations.
• Deep familiarity with cutting-edge ML architectures (e.g., transformer-based models, 2-tower architectures, LLMs and VLMS) and their applications in large-scale Search and Recommender Systems.
• Proven ability to measure, deploy, and refine fairness interventions and broader Responsible AI solutions at scale, bridging state-of-the-art research with tangible product impact.
• 4+ years working experience in the engineering teams that build large-scale ML-driven user-facing products.
• 1+ years experience leading cross-team engineering efforts.
• Masters or PhD in Comp Sci or related fields.

Nice To Have

• Publications at top ML conferences.
• Experience using 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.
• Expertise in scalable realtime systems that process stream data.
• Passion for applied research and the Pinterest product.