Machine Learning Engineer II

. Build cutting-edge technology using advances in deep learning and machine learning to personalize Pinterest .

Posted 10/5/2026full-timeRemote • California • United StatesMid-LevelSenior💰 $215,250 - $285,982 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in deep learning, machine learning, and natural language processing to enhance personalization and recommendation systems. Proven ability to build data processing pipelines and improve ML models across various product surfaces.

Highest-signal resume keywords

Master's Degree In Computer ScienceUser Modeling ExperiencePersonalization ExperienceRecommender Systems ExperienceNatural Language Processing Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Deep LearningMachine LearningReinforcement LearningGraph Representation LearningData Processing PipelinesHadoopSparkRetrieval TargetingSearch And RankingML Model Improvement

Industry Keywords

Recommendation SystemsData-Driven MethodsContent UnderstandingHigh-Impact EnvironmentRapid Experimentation

Tech Stack

Tools & technologies

HadoopSpark

About the role

Key responsibilities & impact

Build cutting-edge technology using advances in deep learning and machine learning to personalize Pinterest
Partner with teams across Pinterest to experiment with and improve ML models for Homefeed, Ads, Growth, Shopping, and Search
Use data-driven methods and Pinterest’s data properties to improve candidate retrieval
Work in a high-impact environment with rapid experimentation and product launches
Keep up with industry trends in recommendation systems
Leverage LLMs to enhance content understanding

Requirements

What you’ll need

Master’s degree (or foreign degree equivalent) in Computer Science, Data Science, Business Analytics, Engineering (any field), or a closely related quantitative discipline
Three (3) years of experience in the job offered or a related occupation
Two years of experience in User Modeling
Two years of experience in Personalization
Two years of experience in Recommender Systems
Two years of experience in Search and Ranking
Two years of experience in Natural language processing
Two years of experience in Reinforcement Learning
Two years of experience in Graph Representation Learning
Two years of hands-on experience building data processing pipelines
Two years of experience with Hadoop and Spark
Two years of experience in Retrieval Targeting
Two years of experience using the latest advances in deep learning and machine learning
Two years of experience improving ML models for various product surfaces
Any suitable combination of education, training and experience is acceptable
US-based applicants only

Benefits

Comp & perks

Equity eligibility
Full-time telecommuting option
Flexible work arrangements
Equal opportunity and legally compliant employment consideration
Medical or religious accommodation support during the application process