PhD University Grad Machine Learning Engineer 2026 (USA)

<div class="content-intro"><p><strong>About Pinterest:</strong></p> <p>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.</p> <p>Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the <a href="https://www.pinterestcareers.com/our-life/pinflex/">flexibility</a> to do your best work. Creating a career you love? It’s Possible.</p></div><p>With more than 570 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers help build personalized experiences to help Pinners create a life they love. With just over 3,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else.</p> <p><strong><br>By applying to this role, you will be considered for multiple roles open across our various ML teams. Please only apply once within the USA or Canada as multiple applications may delay our recruitment process.</strong></p> <p><strong>This is a general posting for multiple roles open across our various ML teams. You will have the opportunity to work on a very large scope of problems in recommender systems, search, ads, ranking, natural language processing, graph representation learning, personalization, etc.</strong></p> <p> </p> <p>As a Machine Learning Engineer at Pinterest, you’ll work on tackling new challenges in machine learning and artificial intelligence. As you kickstart your career at Pinterest, you’ll join our engineering teams as we maneuver through exponential growth and massive scale while building awesome products and features, creating visually rich experiences, spearheading the discovery problem, and pinpointing tomorrow’s engineering challenges. </p> <p><strong><br></strong><strong>What you’ll do:</strong></p> <ul> <li>Contribute to cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems</li> <li>Collect, analyze, and synthesize findings from data and build intelligent data-driven model</li> <li>Write clean, efficient, and sustainable code</li> <li>Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across discovery, ads and search</li> <li>Design, build, and test models to predict engagement for notifications (push, emails, in-app notifications)</li> <li>Build content recommendation systems to power our push, email, and in-app notifications</li> <li>Work on state-of-the-art large-scale applied machine learning projects</li> <li>Scope and independently solve moderately complex problems</li> </ul> <p><strong><br>What we’re looking for:</strong></p> <ul> <li>PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field required</li> <li>Machine Learning experience (ranking, computer vision, NLP, content recommendations, embedding, information retrieval etc)</li> <li>Proficiency in at least one systems language (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)</li> <li>Experience with big data technologies (e.g., Hadoop/Spark) and scalable realtime systems that process stream data</li> <li>Experience in research and in solving analytical problems</li> <li>Strong communicator and team player with the ability to find solutions for open-ended problems.</li> <li><strong>Preferred Qualifications:</strong> <ul> <li>Publications in machine learning, AI, data science, data analytics, statistics, or related technical fields</li> <li>Interest in research and in applying ML to impactful real-world problems on the Pinterest pro ... (truncated, view full listing at source)