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. In your role, 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 Pinners make their lives better in the positive corner of the internet.
Our new progressive work model is called PinFlex, a term that’s uniquely Pinterest to describe our flexible approach to living and working. Visit our PinFlex landing page to learn more.
Shopping is at the core of Pinterest’s mission to help people create a life they love. Pinterest has the unique advantage to build the world's most inspirational, visual and personalized shopping experience for its 450M+ users worldwide. The shopping discovery team is in charge of helping Pinners to discover the most relevant products that they will love. The team works on shopping content recommendations and distribution on various surfaces e.g. product detail page, search, home feed, board etc.
As an engineer of the team you will be working on the most cutting edge ML technologies in the area of search and recommendation. Some of the advanced ML technologies used in search and recommendation are embedding based candidate generation, multi-head deep learning model for ranking, multi-objective utility optimization, explore / exploit etc. You’ll work on the full stack of the ML lifecycle, including model training, serving, running experiments and directly improving the shopping metrics contributing to the bottom line of the company.
You will have an opportunity to work on a variety of ML problems because shopping is cross-cutting and touches all aspects of Pinterest. It is also a largely green-field with lots of opportunities to build things from scratch and have a huge impact because shopping is one of the major expansion areas for Pinterest. If you are excited about large scale machine learning problems in the area of recommendation, search then you must consider this role.
What you'll do:
- Develop context aware and personalized embedding based candidate retrieval algorithms
- Train deep learning models to improve shopping recommendation
- Improve search relevance and ranking models
- Develop ML algorithms and frameworks to balance different objectives and model long term values
- Build data pipelines to do data analysis and collect training data
- Work on backend and infrastructure to build, deploy and serve machine learning models
What we're looking for:
- 3+ years working experience in the area of applied Machine Learning
- Interest or experience working on a large-scale search, recommendation and ranking problems
- Interest and experience in doing full stack ML, including backend and ML infrastructure
- Experience with big data technologies MapReduce/Hadoop/Hive/Presto/Spark
- Expert in Java, C++ or Python
Our Commitment to Diversity:
At Pinterest, our mission is to bring everyone the inspiration to create a life they love—and that includes our employees. We’re taking on the most exciting challenges of our working lives, and we succeed with a team that represents an inclusive and diverse set of identities and backgrounds.