Senior ML Engineer, Personalization & Real-Time Recommendations

Pinterest; United States; Remote; USD 140,000 - 200,000; Full time

Job summary

Pinterest is seeking a machine learning engineer to build cutting-edge personalization using deep learning and ML. You will join a cross-functional team to experiment and improve ML models across product surfaces, leveraging data-driven approaches to enhance candidate retrieval and recommendation quality.

Applicants should have a PhD or equivalent, 1–2 years in ML or software roles, and experience with Java and NLP in production pipelines.

Qualifications

• PhD in Computer Science or related field plus two years of experience, or one year in software/ML role.
• At least one year of experience with Java for scalable backend services powering real-time recommendation pipelines.
• At least one year of experience applying Natural Language Processing to recommendation systems.
• Proficiency in Python and solving analytical problems using quantitative approaches.
• Experience adapting ML methods to distributed clusters, multicore SMP, or GPU.
• Ability to gather, manipulate, and analyze complex, high-volume, high-dimensionality data from varying sources.

Responsibilities

• Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest.
• Partner closely with teams across Pinterest to experiment and improve Machine Learning models for various product surfaces.
• Use data driven methods and leverage the unique properties of our data to improve candidates retrieval.

Skills

Python

Java

NLP

Distributed Systems

Data analysis

Quantitative methods

Education

PhD in Computer Science or related field

Job description

Pinterest is seeking a machine learning engineer to build cutting-edge personalization using deep learning and ML. You will join a cross-functional team to experiment and improve ML models across product surfaces, leveraging data-driven approaches to enhance candidate retrieval and recommendation quality.

Applicants should have a PhD or equivalent, 1–2 years in ML or software roles, and experience with Java and NLP in production pipelines.