Staff Software Engineer, Trends Machine Learning Infrastructure

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 were 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 others unique experiences and embrace theflexibility to do your best work. Creating a career you love Its Possible.

At Pinterest AI isnt just a feature its a powerful partner that augments our creativity and amplifies our impact and were looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities well 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.

The Trends & Insights Engineering team builds the products that turn Pinterests unique signal what hundreds of millions of people are planning dreaming about and shopping for into actionable intelligence for advertisers. As a Staff Software Engineer on this team youll lead the technical evolution of Pinterest Trends and Audience Insights into a unified AI-powered insights platform that shapes how advertisers plan campaigns allocate budget and create content across the Pinterest Ads ecosystem..

What youll do:

• Set the technical direction for a unified audience-first insights platform that powers Pinterest Trends Audience Insights and recommendations embedded across Ads Manager surfaces.
• Architect scalable data pipelines and systems that generate reusable personalized insights from Pinterests trend audience and content signals.
• Lead delivery of high-impact roadmap bets such as Trends Digest Moments Topics expansion and Product Attributes from prototype to production.
• Build LLM-powered capabilities (summarization classification conversational insights agentic review) with strong safety quality and evaluation guardrails.
• Partner with Product Design Data Science and Ads org teams to bring proactive contextual insights into advertiser workflows beyond standalone surfaces.
• Use AI to accelerate prototyping design exploration and code generation iterating across more options earlier while applying engineering judgment and verification to ensure correctness and quality.
• Use AI to synthesize research summarize large datasets and automate repeatable engineering tasks like documentation test generation and data QA checks.
• Mentor engineers across the team raise the technical bar and establish measurement practices that connect insight quality to advertiser adoption and revenue impact.

What were looking for:

• Bachelors degree in Computer Science a related field or equivalent experience.
• 8 years of software engineering experience including significant time designing large-scale data or ML-powered platforms that serve customer-facing products.
• Ability to work with cross-functional partners across multiple organizations.
• Hands-on experience building tools and data pipelines leveraging AI coding tools e.g. Cursor Claude Code Codex etc.
• Experience as the product-engineering counterpart on an AI-first product launch from prototype to scale
• Demonstrated experience using AI to accelerate engineering and analysis workflows with a clear approach to validating accuracy performance and quality.
• Strong track record of critical evaluation and verification of AI-assisted work testing source-checking data validation and peer review.
• Experience leading cross-surface product integrations across multiple teams and organizational boundaries not just standalone tools.

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 understand that optimal work environments are highly situational and vary between departments. Day-to-day expectations shift based on specific organizational needs or the nature of the role.
• In-person collaboration is required once every quarter; candidates must reside within commuting distance of our San Francisco or Palo Alto hubs.

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