Machine Learning Engineer, Knowledge at Pinterest in San Francisco
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.
We have more than 300M monthly active users who actively curate an ecosystem of more than 100B pins (ideas) on more than 1B boards to create a rich human curated graph of immense value. Technically, we are building out an internet scale personalized recommendation engine in 22+ languages, which requires a deep understanding of the users and content on our platform. As an engineer on the Pin Knowledge team, you’ll work on content classification, user modeling, personalization and ranking. Engineers of this team often make measurably positive impact on hundreds of millions of users with improved machine learning modeling and featurization breakthroughs.
What You’ll Do
- Work with a group of friendly and experienced ML engineers to build the next generation ML signal pipeline widely used in Pinterest, including candidate generation, featurization and ranking model improvement.
- Work in a fast-paced environment with a quick cadence of research, experimentation, and product launches
- Design and build systems that combine machine learning and product design to continuously improve over time.
- Partner closely with other product teams across the organization to experiment with different algorithms and validate their effectiveness, while gaining knowledge of how ML works in all these products.
What We’re Looking For
- 3+ years of software engineering/ML expertise and the ability to build scalable systems
- Knowledge of algorithms, data-structures and measurement/statistics.
- Practical experiences in machine learning, natural language processing or information retrieval
- Experience working with large code bases, cross team collaboration, mentoring other engineers, giving and getting feedback, and reviewing code/systems.
- Experience with MapReduce/Hadoop and/or distributed systems.