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

Pinterest Engineering is on a mission to inspire creativity and innovation through their platform. They are seeking a Senior Machine Learning Engineer to lead projects in responsible AI, focusing on fairness and ethical considerations in machine learning applications.

Responsibilities:

• Design and drive projects in the responsible AI frontier to identify, avoid, and mitigate bias across a wide range of ML applications at Pinterest. These include but are not limited to Gen AI product evaluations, foundation models safety fine tuning and alignment, and Red Teaming
• 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

Requirements:

• 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
• 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