PhD University Grad Machine Learning Engineer (USA)

Pinterest•Palo Alto, CA

17h•$174,078 - $229,044•Hybrid

About The Position

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. 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. With more than 640 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. 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. 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. 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. 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.

Requirements

PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field required
Machine Learning experience (ranking, computer vision, NLP, content recommendations, embedding, information retrieval etc)
Experience with big data technologies (e.g., Hadoop/Spark) and scalable realtime systems that process stream data
Mastery of at least one systems languages (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)
Proficiency with AI-native engineering, including the design of agent-friendly codebases.
High degree of autonomy in learning new agent-first development tools.
Strong critical thinking when working with AI-generated suggestions, with a clear approach to validating correctness, performance, security, and maintainability.
Comfort iterating on prompts, refining workflows, and adapting AI-assisted approaches based on the problem, context, and constraints.
Experience in research and in solving analytical problems
Strong communicator and team player. Being able to find solutions for open-ended problems.

Nice To Haves

Publications in machine learning, AI, data science, data analytics, statistics, or related technical fields
Interest in research and in applying ML to impactful real-world problems on the Pinterest product

Responsibilities

Contribute to cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
Collect, analyze, and synthesize findings from data and build intelligent data-driven model
Write clean, efficient, and sustainable code
Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across discovery, ads and search
Design, build, and test models to predict engagement for notifications (push, emails, in-app notifications)
Build content recommendation systems to power our push, email, and in-app notifications
Work on state-of-the-art large-scale applied machine learning projects
Scope and independently solve moderately complex problems