Staff Software Engineer, Growth AI

Pinterest•Los Angeles, CA

1d•$208,454 - $364,795•Hybrid

About The Position

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, we’re 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 other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll 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. Pinterest's Growth org reaches hundreds of millions of users by helping them discover Pinterest from across the web — through search engines, generative engines (ChatGPT, Perplexity, Google AI Overviews), and other emerging surfaces. We're hiring a Staff Software Engineer to be the product engineering anchor across two closely partnered teams: our SEO Product team, which owns Pinterest's durable organic discovery channels, and a new exploratory team focused on AI-first growth products. This is a hands-on technical role for a strong product engineer who wants to architect and ship AI-powered growth experiences at scale, partnering closely with ML teams to take capabilities from prototype to production. You'll set the technical bar through your own code and architecture — not by stepping into management.

Requirements

8+ years of product / systems engineering experience, with a strong track record shipping production systems at scale that touch real users.
Cross-team technical leadership: you've been the architectural anchor on multi-team initiatives, set direction others build on, and mentored through code.
Working knowledge of common ML/AI techniques (supervised learning, embeddings, ranking, LLMs, evaluation methodology) — enough to scope ML projects, reason about ML system design, and collaborate effectively with MLEs.
Strong track record partnering with ML/research teams to ship AI-powered features in production.
Demonstrated AI-augmented engineering practice — fluent use of Cursor / Claude Code / agentic tools, with a clear approach to validating AI-generated work.
Upsell, influence the scope of the team (e.g. cross team collaboration on potential signal sharing and other opportunities )
Bachelor’s/Master’s degree in a relevant field such as Computer Science, or equivalent experience.

Nice To Haves

Direct hands-on experience shipping applied ML, LLM/VLM, or agentic systems in production
Domain experience in search, discovery, recommendations, ranking, growth, or SEO
Experience as the product-engineering counterpart on an AI-first product launch from prototype to scale

Responsibilities

Architect and build the production systems that AI/ML capabilities ship through across two Growth teams: APIs, data pipelines, content systems, evaluation and monitoring infrastructure.
Partner with Pinterest's centralized ML org and applied research teams to productize AI/ML capabilities at scale — defining service interfaces, building eval pipelines, and managing latency, cost, and quality tradeoffs.
Design and build the cross-team technical foundations that serve both teams: AI evaluation systems, content quality pipelines, agent skill platform, knowledge brain.
Set the technical bar across two teams operating an AI-native engineering model: AI in every part of the SDLC, eval-driven shipping, prototype-first culture.
Mentor engineers across both teams as a peer Staff IC, deepening their technical work without managing them.