Pinterest
Verified live 5h ago
Machine Learning Engineer, Monetization Engineering
Brief overview
Seattle, WAIn-person
UndergradOr in progress
$163k–$286k/yrStated range
2+ yrsMinimum
726 H-1B approvalsDept. of Labor
231 green cardsCertified filings
User modelingPersonalizationRecommender systemsSearch and rankingNatural language processingReinforcement learningGraph representation learningBuilding data processing pipelinesLarge scale machine learning systemsBig data technologies (e.g., Hadoop/Spark)Ads ranking and retrievalTargeting and marketplace systemsLLM-powered productivity toolsScalable realtime systemsStream data processingApplied machine learning
About the company
Pinterestpinterest.com
Operates a visual discovery engine for finding creative ideas.
Visa sponsorship history
4 years sponsoring, last filed FY2026
Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.726H-1B approved
99%approval rate
155new H-1B hires
231PERM certified
$165,412median wage / yr
H-1B Petition ApprovalsVisas USCIS actually granted: the strongest sign the company sponsors.
2023156
2024225
2025301
202644
LCA Certified ApplicationsAn early filing step, not a visa approval: it signals intent, not confirmed sponsorship.
202377
202468
202569
202638
Green Card (PERM) FilingsCertified green card filings: a long-term commitment to international hires.
202345
202461
2025115
202610
Top sponsored roles
Machine Learning Engineer IISoftware Engineer IISr. Machine Learning EngineerSr. Software EngineerStaff Machine Learning Engineer
Sponsored employees from
ChinaIndiaCanadaTaiwanMexico
Job description
Summary
Pinterest is a platform that inspires creativity and helps users plan memorable experiences. They are seeking a Machine Learning Engineer to develop and execute a vision for evolving the machine learning technology stack within Ads, focusing on building personalized experiences and improving ML models.
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 ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas
- Use data driven methods and leverage the unique properties of our data to improve candidates retrieval
- Work in a high-impact environment with quick experimentation and product launches
- Keep up with industry trends in recommendation systems
- Leverage LLMs to enhance content understanding
Skills
- 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
- Degree in computer science, machine learning, statistics, or related field
- End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
- Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems
- Publications at top ML conferences
- Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
- Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
- Expertise in scalable realtime systems that process stream data
- Passion for applied ML and the Pinterest product
- Background in computational advertising
Qualifications
Must Haves
- 2+ years of industry experience applying machine learning methods (e.g., user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning)
- Degree in computer science, machine learning, statistics, or related field
- End-to-end hands-on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (e.g., Hadoop/Spark)
- Practical knowledge of large scale recommender systems, or modern ads ranking, retrieval, targeting, marketplace systems
Nice to Haves
- Publications at top ML conferences
- Experience using Cursor, Copilot, Codex, or similar AI coding assistants for development, debugging, testing, and refactoring
- Familiarity with LLM-powered productivity tools for documentation search, experiment analysis, SQL/data exploration, and engineering workflow acceleration
- Expertise in scalable realtime systems that process stream data
- Passion for applied ML and the Pinterest product
- Background in computational advertising
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