Senior Staff Machine Learning Engineer, Applied Science

Pinterest - San Francisco, CA

Full-time - Senior

San Francisco, CA

Professional, Scientific, and Technical Services

About the position

The Senior Staff Machine Learning Engineer in Applied Science at Pinterest is responsible for leading innovative research in machine learning and collaborating with engineering teams to implement solutions that enhance user experience. This role involves tackling complex machine learning challenges that significantly impact how users discover and interact with content on the platform. The engineer will work on various projects, including representation learning, recommender systems, and natural language processing, while also mentoring junior researchers and collaborating with external experts.

Responsibilities

• Lead cutting-edge research in machine learning and collaborate with other engineering teams to adopt innovations into Pinterest problems.
• Collect, analyze, and synthesize findings from data to build intelligent data-driven models.
• Scope and independently solve moderately complex problems; 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.

Requirements

• Mastery of at least one systems language (Java, C++, Python) or one ML framework (Pytorch, Tensorflow, MLFlow).
• Experience in research and in solving analytical problems.
• Strong communicator and team player, able to find solutions for open-ended problems.
• 8+ years of working experience in R&D or engineering teams that build large-scale ML-driven projects.
• 3+ years of experience leading cross-team engineering efforts that improve user experience in products.
• MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences, or related field.

Nice-to-haves

• Strong publication track record and industry experience in shipping machine learning solutions for large-scale challenges.
• Cross-functional collaborator and strong communicator.
• Comfortable solving ambiguous problems and adapting to a dynamic environment.

Benefits

• Equity eligibility
• Base salary range of $158,950—$327,000 USD