Distinguished Machine Learning Engineer, Monetization at Pinterest

Within the Monetization ML Engineering team, we try to connect the dots between the aspirations of Pinners and the products offered by our partners. In this role, you will be responsible for developing and executing a vision for the evolution of the machine learning technology stack within Ads Ranking. You will work on tackling new challenges in machine learning and deep learning to advance the statistical models that power the ads engagement and delivery that bring together Pinners and partners in this unique marketplace. What you'll do:Lead user-facing projects that involve end-to-end engineering development in both frontend and backend and ML.Improve relevance and increase long term value for Pinners, Partners, Creators, and Pinterest through efficient Ads Delivery.Improve our engineering systems to improve the latency, capacity, stability and reduce infra cost.Collaborate with product managers and designers to develop engineering solutions for user-facing product improvements.Collaborate with other engineering teams (infra, user modeling, content understanding) to leverage their platforms and signals. What we're looking for:Experience with large scale data processing (e.g. Hive, Scalding, Spark, Hadoop, Map-reduce).12+ years of industry experience in the engineering teams that build large-scale ML-driven user-facing products.6+ years of technical leadership experience; leading cross-team engineering efforts that improves user experience in products.Strong execution skills in project management.Masters or PhD in computer science, machine learning, statistics, or related fields, or equivalent experience.Strong software engineering and mathematical skills with knowledge of statistical methods.Experience in working in frontend, backend and ML systems for large-scale user-facing products, and have a good understanding of how they all work.Experience in closely collaborating with product managers/designers to ship ML-driven user-facing product.Hands-on experience with large-scale online e-commerce systems is a plus.Background in computational advertising is preferred. Relocation Statement:This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model. In-Office Statement:We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.This role will need to be in the office for in-person collaboration 1-2 times/month and therefore can be situated anywhere in the country.#LI-HYBRID#LI-SM4