Pinterest

PhD Machine Learning Intern role focused on developing and launching new user features using ML techniques in recommendation systems, computer vision, generative AI, and responsible AI. The role involves research, production ML systems, and leveraging frontier AI tools, with potential for paper submissions or deploying features to millions of users.

VP, Ads Quality Engineering to spearhead the AIML engineering division, leveraging data, machine learning, and generative AI to enhance Pinterest's ads delivery funnel. This role requires strong analytical skills, deep understanding of ML and generative AI, online auction dynamics, and experience leading large engineering teams to maximize monetization opportunities.

Engineering Manager I on Pinterest’s Growth AI Products team, leading a group of engineers building AI-led products and capabilities that drive top-of-funnel growth. The role involves shipping user-facing experiences and AI-powered content representation improvements, partnering closely with product, design, analytics and ML teams. Responsibilities include owning the team's roadmap, driving AI-led innovations, establishing launch readiness standards for AI-powered features, and improving team operating cadence using AI.

Machine Learning Engineer II at Pinterest focused on building and improving ML models for core product surfaces like Homefeed, Ads, Growth, Shopping, and Search. The role involves developing cutting-edge deep learning and ML technologies for personalization, using data-driven methods, and working with large-scale systems and stream data. The primary output is the improvement and deployment of ML models within the consumer product.

Product Manager for AI/ML solutions focused on merchant presence and shopping experiences on Pinterest, utilizing LLMs to identify and surface relevant merchants, aiming to increase Pinner discovery of new brands and help merchants build diverse audiences. The role involves defining, designing, and launching AI/ML-powered experiences, partnering cross-functionally, setting product vision, and identifying opportunities to advance personalization.

Machine Learning Engineer II at Pinterest focused on developing and implementing ML models for user targeting and personalization to drive engagement and growth. The role involves building scalable ML pipelines, conducting A/B tests, analyzing data, and contributing to ML infrastructure, with an emphasis on leveraging AI tools for engineering practices.

Director of Product Management for Personalized Experiences at Pinterest, focusing on AI/ML-powered features for user discovery, curation, and shopping. This role involves defining product vision, strategy, and requirements, partnering with cross-functional teams to deliver scalable consumer products.

Director of Machine Learning Engineering for the Growth organization at Pinterest. This role will define the long-term ML vision, strategy, and operating model to drive user and engagement growth. Responsibilities include overseeing multiple ML teams, partnering with leadership on strategy, defining ML architecture, building and developing teams, and acting as a thought partner. The role requires deep expertise in building and operating large-scale ML systems in production, leading multiple ML teams, and defining technical strategies.

Manager II, Machine Learning-Search at Pinterest, leading a team responsible for major areas of the search engine, including indexing, ranking, query understanding, personalization, ML-based retrieval, shopping, videos, and infrastructure efficiency. The role involves innovative applications of NLP and Vision Models for query recommendations, multimodal search, agentic search, and query-based module generation. Requires experience leading large-scale production ML systems and applied ML experience.

Product Manager for AI/ML Personalization at Pinterest, focusing on driving the future of personalized experiences on the platform. This role involves defining, designing, and launching AI/ML-powered features for user discovery, curation, and shopping, partnering with Engineering, Data Science, and Design to deliver impactful products on high-traffic surfaces.

Staff Data Scientist at Pinterest focused on the Engagement Ecosystem. The role involves developing and productionizing ML frameworks for forecasting, recommendation, and causal inference, applying advanced ML and generative AI techniques to model complex interactions, and championing responsible AI use. Requires expertise in ML, causal inference, experimentation, and large-scale data environments, with a track record of influencing product decisions and mentoring junior scientists.

Manager II, Machine Learning Engineering for Core Engineering at Pinterest, focusing on search and recommendations for over 500 million users. The role involves leading a team of ML engineers, driving technical direction, strategic planning, and execution for large-scale, low-latency systems and state-of-the-art ML models that deliver significant impact to pinners and business metrics.

Machine Learning Engineer at Pinterest focused on building and improving ML models for various product surfaces like Homefeed, Ads, Growth, Shopping, and Search. The role involves using data-driven methods to enhance candidate retrieval and working with large-scale recommendation systems.

Machine Learning Engineer at Pinterest focused on building and improving ML models for various product surfaces like Homefeed, Ads, Growth, Shopping, and Search, leveraging deep learning and large-scale data to personalize user experiences.

Machine Learning Engineer focused on Monetization at Pinterest, building and improving ML models for various product surfaces like Homefeed, Ads, Growth, Shopping, and Search. The role involves developing cutting-edge deep learning and ML technology for personalization, leveraging data for candidate retrieval, and enhancing content understanding with LLMs. Experience with large-scale recommender systems, ads ranking, and big data technologies is required.

Machine Learning Engineer focused on personalization and monetization within the consumer domain, specifically for Pinterest's ad platform. The role involves building and improving ML models for various product surfaces, leveraging data for candidate retrieval, and enhancing content understanding with LLMs. It requires end-to-end experience with ML systems and a practical understanding of recommender systems or ad ranking.