Staff ML Engineer, Applied Research & LLMs

Pinterest; San Francisco (CA); On-site; USD 189,308 - 389,753; Full time

Job summary

Pinterest Labs is hiring for an advanced ML researcher to push the boundaries of machine learning and multi-modal LLMs across Pinterest's platform. You will work with a world-class team of researchers and engineers to translate research into practical, impactful solutions for search, discovery, and recommendations.

The role emphasizes rigorous experimentation, collaboration across teams, and the ability to explain your approach and reasoning throughout the interview process.

Qualifications

• MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field.
• 6+ years of industry experience.
• Experience in machine learning/information retrieval.
• Experience in research and in solving analytical problems.
• Cross-functional collaborator and strong communicator.
• Comfortable solving ambiguous problems and adapting to a dynamic environment.

Responsibilities

• Contribute to cutting-edge research in machine learning and LLM that can be applied to Pinterest problems, especially search and recommendation agents.
• Collect, analyze, and synthesize findings from data and build intelligent data-driven models.
• Write clean, efficient, and sustainable code.
• Use ML, NLP, and graph analysis to solve modeling and ranking problems across growth, discovery, ads and search.
• Scope and independently solve moderately complex problems.

Skills

Machine learning

Information retrieval

Programming: Java/C++/Python

Communicator

Ambiguity tolerance

Education

MS/PhD in Computer Science, ML, NLP, Statistics, Information Sciences or related field

Tools

Tensorflow

PyTorch

MLFlow

Job description

Pinterest Labs is hiring for an advanced ML researcher to push the boundaries of machine learning and multi-modal LLMs across Pinterest's platform. You will work with a world-class team of researchers and engineers to translate research into practical, impactful solutions for search, discovery, and recommendations.

The role emphasizes rigorous experimentation, collaboration across teams, and the ability to explain your approach and reasoning throughout the interview process.