Opportunity at
PinterestMachine Learning Engineer, Monetization Engineering
Pinterest operates a visual discovery platform serving more than 600 million global users who save ideas. The company employs over 4,000 staff members worldwide and is…
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About This Role
Pinterest operates a visual discovery platform serving more than 600 million global users who save ideas. The company employs over 4,000 staff members worldwide and is currently hiring a Machine Learning Engineer to join the Monetization Engineering division located in San Francisco. This on-site position focuses on bridging user aspirations with partner offerings through the evolution of the machine learning technology stack within Ads. Practitioners in this role will build…
Job Description
Pinterest operates a visual discovery platform serving more than 600 million global users who save ideas. The company employs over 4,000 staff members worldwide and is currently hiring a Machine Learning Engineer to join the Monetization Engineering division located in San Francisco.
This on-site position focuses on bridging user aspirations with partner offerings through the evolution of the machine learning technology stack within Ads. Practitioners in this role will build advanced personalization technology, refine candidate retrieval processes using data-driven techniques, and leverage large language models to improve content understanding. The team operates in a fast-paced setting characterized by rapid experimentation and product deployment.
Ideal candidates possess a background in applied machine learning and scalable data systems, and they must be based in the United States. While the role follows a hybrid arrangement, relocation assistance is not available for this opening.
Responsibilities
- Develop advanced technology utilizing deep learning and machine learning innovations to personalize user experiences.
- Collaborate across company teams to test and optimize machine learning models on Homefeed, Ads, Growth, Shopping, and Search surfaces.
- Apply data-driven approaches and leverage proprietary data characteristics to enhance candidate retrieval.
- Operate within a high-impact environment focused on rapid experimentation and frequent product launches.
- Stay informed regarding industry developments concerning recommendation systems.
- Utilize large language models to improve content comprehension.
Requirements
- Minimum of two years of professional experience applying machine learning methods such as user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning.
- Hands-on, end-to-end experience building data processing pipelines, large-scale machine learning systems, and big data technologies including Hadoop or Spark.
- Practical familiarity with large-scale recommender systems, modern ads ranking, retrieval, targeting, or marketplace systems.
Qualifications
- Bachelor's degree in computer science, machine learning, statistics, a related discipline, or equivalent practical experience.
- Published papers at top machine learning conferences.
- Experience utilizing AI coding assistants such as Cursor, Copilot, or Codex for development, debugging, testing, and refactoring.
- Familiarity with large language model-powered productivity tools for documentation search, experiment analysis, SQL and data exploration, and engineering workflow acceleration.
- Expertise in scalable real-time systems capable of processing stream data.
- Background in computational advertising.
Core Skills
Benefits
- Base salary range between $163,418 and $285,982 USD for US-based applicants
- Eligibility for equity
Frequently Asked Questions
What is the location and work model for this position?
The position is based in San Francisco, California, and is an on-site, hybrid role intended for US-based applicants only.
Is relocation assistance provided?
No, this job opening is not eligible for relocation assistance.
What is the salary range for this role?
The base salary range spans from $163,418 to $285,982 USD, and the position is also eligible for equity.
What are the core educational requirements?
Applicants must hold a bachelor's degree in computer science, machine learning, statistics, a related field, or possess equivalent experience.
Sample Interview Questions
AI-generated questions tailored to this specific role — a preview of the full practice set.