10 months ago
Toronto, CanadaMid Level
Responsibilities
- Build deep learning and machine learning technology to personalize Pinterest.
- Partner with teams across Pinterest to experiment on and improve ML models for Homefeed, Ads, Growth, Shopping, and Search.
- Use data-driven methods and Pinterest’s data to improve candidate retrieval.
- Work in a high-impact environment with rapid experimentation and product launches.
- Keep up with industry trends in recommendation systems.
Requirements
- At least 2 years of industry experience applying machine learning methods such as user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, or graph representation learning.
- End-to-end hands-on experience building data processing pipelines, large-scale machine learning systems, and big data technologies such as Hadoop and Spark.
- M.S. or PhD in machine learning or a related area.
- Expertise in scalable real-time systems that process streaming data.
- Passion for applied machine learning and the Pinterest product.
Benefits
- Remote-oriented work model with in-office collaboration 1–2 times per quarter.
- Must be within commuting distance of Pinterest’s Toronto office at 85 Richmond St. W.
- Relocation assistance is not available.
Tech Stack
Apache HadoopApache Spark
Categories
Data EngineeringML Engineering
About Pinterest
Pinterest builds a visual discovery and bookmarking platform where people search, save, and shop ideas across home, fashion, food, and more. The company monetizes primarily through advertising and shopping integrations, using visual search and recommendation systems to connect users and merchants. Founded in 2010 and headquartered in San Francisco, Pinterest is a public company on the NYSE (PINS) with around 482 million monthly users worldwide.