Pinterest Opens PhD-Level Machine Learning Engineer Roles for University Graduates in the USA (2026)

Pinterest has announced new PhD University Graduate Machine Learning Engineer roles for 2026, opening doors for early-career researchers to work on large-scale AI systems that power one of the world’s most influential discovery platforms.

The positions are based in San Francisco, Palo Alto, and Seattle, with a hybrid work model and compensation reaching over $214,000 per year, plus equity.

Why This Pinterest Role Stands Out

With more than 570 million global users and over 300 billion ideas saved, Pinterest operates at a scale where machine learning decisions directly shape how people discover, plan, and create. Unlike many entry-level roles, this opportunity places PhD graduates directly into core ML teams working on real-world, high-impact systems.

Pinterest’s ML engineers don’t just tune models—they define how inspiration is ranked, recommended, and delivered across the platform.

Role Overview: Machine Learning Engineer (PhD University Grad)

This is a general hiring post covering multiple machine learning teams at Pinterest. Selected candidates may work across areas such as:

• Recommender systems and personalization

• Search, ranking, and ads optimization

• Natural language processing (NLP)

• Graph representation learning

• Large-scale engagement prediction models

By applying once, candidates are considered across all eligible ML teams in the United States.

What You’ll Work On at Pinterest

As a Machine Learning Engineer, you’ll contribute to both research-driven innovation and production-level systems, including:

• Designing and deploying ML models for content discovery and recommendations

• Building engagement prediction systems for push, email, and in-app notifications

• Applying NLP and graph-based learning to ranking and relevance problems

• Working with massive datasets to build intelligent, data-driven solutions

• Writing clean, scalable, and sustainable production code

• Independently solving complex modeling and engineering challenges

This role blends academic depth with real-world impact—ideal for PhDs transitioning from research to applied AI.

Eligibility and Required Qualifications

Pinterest is specifically targeting recent or upcoming PhD graduates who bring strong research foundations into applied machine learning.

Required:

• PhD in Computer Science, Machine Learning, NLP, Statistics, Information Sciences, or a related field

• Experience in machine learning domains such as ranking, NLP, embeddings, computer vision, or recommendations

• Proficiency in at least one programming language or ML framework (Python, Java, C++, TensorFlow, PyTorch, MLflow)

• Experience working with large-scale data systems (Hadoop, Spark, streaming pipelines)

• Strong analytical thinking and problem-solving skills

Preferred:

• Peer-reviewed publications in ML, AI, or data science

• Interest in applying research to real-world, user-facing products

Work Location and Flexibility

Pinterest follows a hybrid collaboration model. While day-to-day work may be flexible, this role requires candidates to live within commuting distance of a Pinterest office for key collaboration moments.

Locations include:

• San Francisco, CA

• Palo Alto, CA

• Seattle, WA

US-based applicants only.

Salary, Equity, and Benefits

Pinterest has disclosed a transparent compensation range for this role:

• Base Salary: $162,690 – $214,060 USD

• Additional Compensation: Equity eligibility

• Final compensation depends on location, experience, and skill set

Pinterest is widely known for competitive benefits, inclusive workplace policies, and strong support for employee growth.

Commitment to Inclusion

Pinterest emphasizes an equitable and inclusive hiring process, evaluating candidates strictly on merit and qualifications. The company actively supports accommodations during the hiring process and complies with all US employment laws.

A Rare Opportunity for PhD Graduates in AI

For PhD graduates aiming to apply machine learning research at global scale, this Pinterest opportunity offers something rare: academic-level problems, production-level systems, and consumer-level impact—all in one role.

As recommendation systems, discovery engines, and AI-driven creativity continue to shape the internet, Pinterest is positioning its ML engineers at the center of that transformation.