As Pinterest Labs, you'll work on tackling new challenges in machine learning and artificial intelligence along with a world-class team of research scientists, and machine learning engineers. You'll conduct research that can be applied across Pinterest engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: computer vision, graph neural network, natural language processing (NLP), inclusive AI, reinforcement learning, user modeling, and recommender systems.

What you’ll do:

• Contribute to cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
• Collect, analyze, and synthesize findings from data and build intelligent data-driven model
• Write clean, efficient, and sustainable code
• Use machine learning, natural language processing, and graph analysis to solve modeling and ranking problems across growth, discovery, ads and search
• Scope and independently solve moderately complex problems

What we’re looking for:

• MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field
• 1-2 years of internship or professional experience
• Experience in machine learning/information retrieval 
• Mastery of at least one systems languages (Java, C++, Python) or one ML framework (Tensorflow, Pytorch, MLFlow)
• Experience in research and in solving analytical problems
• Cross-functional collaborator and strong communicator
• Comfortable solving ambiguous problems and adapting to a dynamic environment

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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