Machine Learning Engineer II

Job Location:

Toronto - Canada

Monthly Salary: Not Disclosed

Posted on: 16 hours ago

Vacancies: 1 Vacancy

Job Summary

With more than 500 million users around the world and 300 billion ideas saved Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 3000 global employees our teams are small mighty and still growing. At Pinterest youll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you wont find anywhere else.

What youll do:

Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest
Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed Ads Growth Shopping and Search) while gaining knowledge of how ML works in different areas
Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
Work in a high-impact environment with quick experimentation and product launches
Keeping up with industry trends in recommendation systems

What were looking for:

2 years of industry experience applying machine learning methods (e.g. user modeling personalization recommender systems search ranking natural language processing reinforcement learning and graph representation learning)
End-to-end hands-on experience with building data processing pipelines large scale machine learning systems and big data technologies (e.g. Hadoop/Spark)
M.S. or PhD in Machine Learning or related areas
Expertise in scalable realtime systems that process stream data
Passion for applied ML and the Pinterest product

Relocation Statement:

This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement:

We let the type of work you do guide the collaboration style. That means were not always working in an office but we continue to gather for key moments of collaboration and connection.
This role will need to be in the office for in-person collaboration 1-2 times per quarter and therefore needs to be in a commutable distance from the Toronto office (85 Richmond St. W).

#LI-REMOTE

Required Experience: