Millions of people across the world come to Pinterest to find new ideas every day. It's where they get inspiration, dream about new possibilities and plan for what matters most. Our mission is to help those people find their inspiration and create a life they love. As a Pinterest employee, you'll be challenged to take on work that upholds this mission and pushes Pinterest forward. You'll grow as a person and leader in your field, all the while helping users make their lives better in the positive corner of the internet.
As an Applied Scientist at Pinterest Labs, you'll work on tackling new challenges in machine learning and deep learning applied to a unique Pinterest dataset of 250 billion pins. You'll work on hard machine learning problems, push the state of the art, and conduct research that can be applied across Pinterest engineering teams and engage in collaborations and mentoring. You'll have the opportunity to perform research in the following areas: representation learning, graph embeddings, image recognition, user modeling, recommender systems, natural language processing, and big data analytics.
What you'll do:
Push the state of the art and apply the latest advances in deep learning and machine learning to improve Pinterest
Impact hundreds of millions of users by developing the next generation of visual discovery technology
Develop machine learning solutions for real world, large-scale problems on the largest visually curated dataset on the planet
Work in a fast-paced environment with a quick cadence of research, experimentation, and product launches
What we're looking for:
Passionate about applied machine learning and deep learning
5+ years experience applying deep learning methods in settings like recommender systems, time-series, user modeling, image recognition, graph representation learning, natural language processing.
Strong passion for research and extensive experience in solving hard analytical problems
Publications in machine learning, AI, data science, data analytics, statistics, or related technical fields
Industry experience in deploying ML/DL models into production (familiarity with scalability/latency/portability concerns, experience with experimentation and hyperparameter tuning)