Machine Learning Engineer, Core Engineering

About the Role

Pinterest's Core Engineering team builds personalized experiences and large-scale recommendation systems for a platform with more than 500 million users and 300 billion saved ideas.

Responsibilities

• Build technology using advances in deep learning and machine learning to personalize Pinterest.
• Partner with teams across Homefeed, Ads, Growth, Shopping, and Search to experiment with and improve ML models.
• Use data-driven methods and the unique properties of Pinterest's data to improve candidate retrieval.
• Work in a high-impact environment with rapid experimentation and product launches.
• Keep up with industry trends in recommendation systems.

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.
• End-to-end hands-on experience building data processing pipelines and large-scale machine learning systems, and working with big data technologies such as Hadoop or Spark.
• Bachelor's degree in computer science, machine learning, statistics, or a related field, or equivalent experience.

Preferred Qualifications

• Master's degree or PhD in machine learning or related areas.
• 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.

Location and Compensation

• Locations: San Francisco, CA; Palo Alto, CA; Seattle, WA; or remote within the US.
• US-based applicants only.
• Base salary range: $138,905–$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 thinking.
• Application and hiring-process information must be true, accurate, and complete. False statements, omissions, or misrepresentations may lead to disqualification or termination after hire.
• Applicants may request medical or religious accommodations during the application process.