Sr. Staff Machine Learning Engineer, Homefeed

Pinterest helps Pinners discover and do what they love. Homefeed is literally the first surface Pinners see when they open the app and so it forms the front-and-center of the Pinterest experience for 400M+ pinners every month. The Homefeed Relevance team’s mission is to recommend inspiring & engaging pins for all our Pinners. We are looking for a Tech Lead Architect who can drive cross-team engineering efforts for shipping ML-driven product experiences to our pinners. You'll have the opportunity to work on various innovative projects of new product experiences, build large-scale low-latency systems and state-of-the-art machine learning models, and deliver great impact to our pinners and business metrics.

What you'll do:

• Improve relevance and the user experience on Homefeed
• Work on state-of-the-art large-scale applied machine learning projects
• Improve the efficiency and reliability of large-scale data processing and ML inference pipeline
• Improve our engineering systems to improve the latency, capacity, stability and reduce infra cost

What we're looking for:

• Languages: Python, Java
• Machine Learning: PyTorch, Tensorflow
• Big data processing: Spark, Hive, MapReduce
• 7+ years experience with Recommender system or User modeling, implementing production ML systems at scale
• 7+ years experience with large scale distributed backend service
• Experience in working in Deep learning and Generative AI models
• Experience in closely collaborating with product managers / designers to ship ML-driven user-facing product 
• Bachelors in computer science or equivalent experience

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 we're 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/quarter and therefore can be situated anywhere in the country.

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