Manager II, Machine Learning – Conversion Visibility

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 way you work best. 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.

What you’ll do:

• Attract, hire, develop, and lead a hybrid team of ML engineers and backend software engineers, fostering strong collaboration across modeling and infrastructure and building an inclusive, high-performing environment where the team can deliver end-to-end solutions.
• Lead a team responsible for the strategy, execution, and operational excellence of identity and conversion signal modeling systems (e.g., user match prediction, conversion type/value prediction, probabilistic attribution and deduplication) that improve match precision/recall and downstream conversion quality across web and app surfaces.
• Partner closely with product managers, data scientists, and tech leads to shape problem definitions, translate business needs into technical strategy, and drive execution toward high-impact outcomes.
• Collaborate closely with Ads Ranking & Bidding, Measurement Products, and Conversion Ingestion & Attribution teams to define interfaces, SLAs, and success metrics that enable end-to-end identity and conversion visibility systems—including models, data pipelines, and serving surfaces—to integrate cleanly into the broader ads ecosystem.
• Establish engineering best practices across both ML and backend development, including data quality, feature and data pipelines, model evaluation, experimentation, service reliability, and operational excellence, so the team can build trustworthy ML-powered systems end to end.
• Use AI to accelerate analysis and iteration on model ideas and architectures, while applying strong judgment, testing, and verification to ensure correctness, reliability, and advertiser trust.

What we’re looking for:

• 7+ years of experience building and deploying large-scale ML systems in production (e.g., ads, measurement, recommendation, ranking, or search).
• 2+ years of experience as an engineering manager or technical lead for an ML engineering team.