Machine Learning Engineer, EPD Ads

About the Role

Pinterest's EPD (Engineering, Product, and Design) Ads ML Engineering team connects Pinners' aspirations with partners' products. You will develop and execute a vision for the evolution of the machine learning technology stack within Ads, contributing to large-scale personalized recommendation systems.

Responsibilities

• Build 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 the unique properties of Pinterest's data to improve candidate retrieval.
• Support rapid experimentation and product launches in a high-impact environment.
• Keep up with industry trends in recommendation systems.
• Leverage large language models to enhance content understanding.

Qualifications

• At least 2 years of industry experience applying machine learning methods, such as user modeling, personalization, recommender systems, search, ranking, natural language processing, reinforcement learning, and graph representation learning.
• Bachelor's degree in computer science, machine learning, statistics, a related field, or equivalent experience.
• End-to-end, hands-on experience building data processing pipelines and large-scale machine learning systems, including big data technologies such as Hadoop or Spark.
• Practical knowledge of large-scale recommender systems or modern ads ranking, retrieval, targeting, and marketplace systems.

Preferred Qualifications

• 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 real-time systems that process streaming data.
• Passion for applied ML and the Pinterest product.
• Background in computational advertising.

Location and Compensation

• Hybrid position with listed locations in San Francisco, CA; Palo Alto, CA; and Seattle, WA.
• US-based applicants only.
• Annual base salary range: $163,418–$285,982 USD. Final salary depends on factors including location, travel, relevant experience, skills, and expertise.
• Eligible for equity.
• Relocation assistance is not available.

Interview and Application Requirements

• Interviews explore foundational skills and how candidates collaborate with AI. Candidates must be able to explain their approach and reasoning.
• Medical or religious accommodations during the application process may be requested through the employer's support form.
• Applicants must certify that information provided throughout the hiring process is true, accurate, and complete. False statements, omissions, or misrepresentations may result in disqualification or termination after hire.