Manager II, Machine Learning-Content Success

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 . Pinterest helps Pinners discover and do what they love. The Content Success team is responsible for ensuring that Pinners see fresh new products, ideas and inspiration in their recommendations and that Content Producers receive value from the platform through exposure, engagement and monetization. We work across different recommendation surfaces (Homefeed, Search, Related Pins, Ads) to develop new integrations and signals. We are looking for an experienced Engineering Manager who can drive the team’s technical direction, lead the team in developing new integrations and signals for recommendation systems and make an impact on Pinterest’s topline metrics. What you'll do: Lead, mentor and grow a team of experienced backend and machine learning engineers in developing advanced signals, integrations and systems, which are integral to key Pinterest products across Discovery, Ads, and Growth. Provide thought leadership in content distribution and recommender systems by setting a long-term technical vision and advancing the state-of-the-art in the field. Act as the glue between content acquisition and recommendation pods becoming the expert in both these areas. Manage project execution and stakeholder communication, including roadmap planning, technical decision-making, risk mitigation, and progress updates to achieve business goals. Help the team solve difficult technical challenges such as: How to build new ML systems, candidate generators, features and models that can handle millions of new Pins every day with low latency to

Required Skills