Machine Learning Engineer II - Content Quality

Our team

We build components that play a key role in the model lifecycle. Active Learning reinforces signal performance on optimal training data. Streaming and batch signal delivery components improve signal integration across all of the user facing surfaces at Pinterest. The team works on key company objectives and is responsible for key metrics. To scale our systems we leverage Spark, Flink, and low-latency model serving infrastructure.

What you'll do:

• Architect and develop systems, data pipelines, tools that accelerate model life cycle

• Collaborate with signal owners during conceptualization and productionization of signals

• Work with infrastructure and platform teams to build the right set of tools and APIs to support signal hosting and delivery

• Collaborate with signal consuming teams to facilitate signal adoption

What we're looking for:

• 2+ years of industry experience

• Expertise in at least one of the generic programming languages (Java/Scala/C++/Python)

• Expertise with machine learning modeling lifecycle

• Hands-on experience in building and debugging scalable backend services and APIs

• Hands-on experience with large-scale distributed systems (distributed storage systems, stream processing, inference, and deployment at scale)

• Strong ability to work cross-functionally and with partner engineering teams

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.

Relocation Statement:

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

#LI-REMOTE #LI-AK7