Pinterest

StaffMachineLearningEngineer

$189–390k Palo Alto, California, United States
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Staff candidates.

The Brief

“Staff Machine Learning Engineer at Pinterest. Skills: Machine Learning, Agentic AI, Recommendation Systems. Lead ML strategy. Lead ML execution”

What You'll Achieve.

Drive advertiser growth; Transform insight to action

Industry & Context.

Problems you'll solve

Troubleshoot campaign performance; Clarify ambiguous spaces

Eligibility Requirements

In office 1 day/week, Commutable distance

What They're Looking For.

Must Have

7+ years ML systems production, End-to-end ML ownership, Solid software engineering skills, Degree in CS or related, Equivalent experience accepted, Deep recommendation system understanding, Proven Staff-level technical leadership, Aligning stakeholders on priorities, Excellent cross-functional communication, Building partnerships with teams, Experience using AI coding assistants, Experience with LLM productivity tools

Nice to Have

Experience with Cursor, Experience with Claude Code

What You'll Do.

Build recommendation systems

Build context foundations

Understand advertiser goals

Understand seller goals

Surface next-best action

Learn from user response

Lead design of systems

Lead implementation of systems

Power proactive guidance

Transform data into signals

Own recommendation initiatives

Develop feature pipelines

Develop evaluation loops

Measure recommendation quality

Measure business impact

Measure failure modes

Improve agent behavior

Use AI to accelerate analysis

Use AI to accelerate prototyping

Use AI to accelerate documentation

Use AI to accelerate experimentation

Ensure customer trust

Ensure responsible AI usage

Ensure production-quality systems

How You'll Work.

Team & Collaboration

Cross-functional teams; Product teams; Data science teams; Infra teams; Partner ML teams; Senior stakeholders

Communication Scope

Cross-functional communication; Stakeholder alignment

Process & Methodology

Roadmap planning

Full Job Description

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, 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. The Advertiser and Seller Experience team builds intelligent systems that help Pinterest advertisers and sellers move from insight to action. Our work spans advertiser-facing products such as Ads Manager as well as internal seller productivity tools that help sales teams identify opportunities, prepare customer conversations, troubleshoot campaign performance, and drive advertiser growth. As a Staff Machine Learning Engineer focused on Agentic AI & Recommendations, you will lead the ML strategy and execution for the intelligence layer behind these experiences. You will build recommendation systems, context foundations, and feedback loops that help AI agents understand advertiser and seller goals, surface the right next-best action, and learn from user response over time. This is a high-impact Staff IC role for someone who wants to combine deep recommen

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