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Pinterest is a visual discovery platform where people find inspiration, save ideas, and organize them around interests, projects, and purchases. Its experience combines personalized recommendations and visual search across topics such as home design, fashion, recipes, and events, while also helping creators and retailers reach audiences through commerce tools and advertising.
Machine Learning Engineer II at Pinterest (California Remote)
Develop deep-learning personalization for Pinterest’s Homefeed, Ads, Shopping, and Search. Improve retrieval, recommendation systems, and content understanding through machine learning and LLMs.
United States
California$215,250 – $285,982 / year
RemoteFull-timeMiddleSeniorEnglish RequiredMachine Learning EngineerDescription
- Develop personalization technology using deep learning and machine learning advances
- Collaborate across Pinterest to test and enhance models for Homefeed, Ads, Growth, Shopping, and Search
- Apply data-driven techniques and Pinterest data to improve candidate retrieval
- Support rapid experimentation and high-impact product launches
- Track developments in recommendation systems
- Use large language models to strengthen content understanding
Requirements
- Master’s degree, or foreign equivalent, in Computer Science, Data Science, Business Analytics, Engineering, or a closely related quantitative field
- At least three years of experience in the offered role or a related occupation
- At least two years of experience with user modeling
- At least two years of experience in personalization
- At least two years of experience with recommender systems
- At least two years of experience in search and ranking
- At least two years of experience in natural language processing
- At least two years of experience in reinforcement learning
- At least two years of experience in graph representation learning
- At least two years of hands-on experience developing data processing pipelines
- At least two years of experience with Hadoop and Spark
- At least two years of experience in retrieval targeting
- At least two years of experience applying current deep learning and machine learning advances
- At least two years of experience improving machine learning models across product surfaces
- Any suitable combination of education, training, and experience is acceptable
- Applicants must be based in the United States
Benefits
- Eligibility for equity
- Option to work remotely full time
- Flexible work arrangements
- Equal opportunity and legally compliant employment consideration
- Support for medical or religious accommodations during the application process
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