Sr. Staff Software Engineer, AI Platform

Pinterest•Palo Alto, CA
•$208,592 - $429,454•Hybrid

About The Position

The AI Platform team delivers essential tools and infrastructure utilized by hundreds of AI and ML engineers across Pinterest, powering crucial functions such as recommendations, ads, visual search, growth/notifications, and trust and safety. Our primary objectives are to ensure AI and ML systems maintain production-grade quality and enable rapid iteration for our customers. As a Senior Staff Software Engineer on the AI Platform team, you will shape and scale Pinterest’s AI/ML evaluation platform into a unified, reliable system adopted company-wide. You will identify modernization opportunities, elevate the roadmap, and execute technical strategy of a durable evaluation system for GenAI and ML workloads at Pinterest, partnering across engineering, research, product, and safety to improve quality, launch decisions, and trust in AI-powered experiences.

Requirements

  • 3+ years of deep, hands-on experience designing and operating evaluation systems for GenAI and complex ML systems, including benchmark design, golden datasets, automated metrics, human evaluation, model-based grading, and failure analysis
  • Strong programming skills in Python coupled with a solid grasp of distributed systems principles, and comfortable iterating with AI tools on coding and design
  • Deep familiarity with GenAI and RecSys evaluation libraries and frameworks, AutoEvals, OpenEvals, Ragas, etc
  • 5+ years of experience building scalable platforms for distributed experimentation, data and model versioning, orchestration, observability, release management, and production monitoring
  • Strong judgment around GenAI risks, including robustness, bias, privacy, security, and the limitations of automated evaluation signals
  • Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience

Responsibilities

  • Identify modernization opportunities and scale the roadmap for a company-wide evaluation system in partnership with technical leadership
  • Define cross-team technical strategy, align partner teams, and drive broad adoption of shared evaluation capabilities
  • Make durable architectural decisions that improve the user experience and reliability of Pinterest’s AI/ML evaluation platform
  • Establish evaluation methodologies and standards that balance automated metrics, expert judgment, human feedback, safety, and business outcomes
  • Lead complex cross-team workstreams, resolve technical tradeoffs and risks, and deliver impact

Benefits

  • equity
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