ML Engineer — Recommender Systems & AI Innovation (Equity)

Pinterest; Palo Alto (CA); On-site; USD 146,000 - 196,000; Full time

Benefits offered by this job

Equity

Job summary

Pinterest is seeking a Machine Learning Engineer to advance large-scale recommender systems and AI-driven experiences. You will tackle challenges across discovery, ads, and search, building and evaluating models to optimize engagement and content recommendations.

The role requires a Master’s in a relevant field, strong ML/NLP/IR skills, experience with big data tools, and proficiency in Python/Java/C++. Collaboration with AI-native engineering is essential in a fast-growing environment.

Qualifications

• Master’s in Computer Science, ML, NLP, Statistics, Information Sciences or related field required.
• Strong ML experience in ranking, computer vision, NLP or content recommendations.
• Experience with big data technologies (Hadoop/Spark) and scalable realtime systems.
• Proficiency in at least one systems language (Java, C++, Python) or one ML framework (TensorFlow, PyTorch, MLFlow).
• Ability to design AI-native, agent-friendly, scalable engineering solutions.

Responsibilities

• Contribute to cutting-edge research in ML/AI applicable to Pinterest problems.
• Collect, analyze, and synthesize data-driven findings to build intelligent models.
• Write clean, efficient, and scalable code.
• Apply ML, NLP, and graph analysis to modeling and ranking across discovery, ads, and search.
• Design, build, and test models to predict engagement for notifications.
• Build content recommendation systems powering push, email, and in-app notifications.
• Work on large-scale applied ML projects and independently solve moderately complex problems.

Skills

ML research

rank­ing/recommendation systems

NLP

embedding

information retrieval

big data tech

Java

C++

Python

TensorFlow

PyTorch

MLFlow

Education

Master’s in CS/ML related field

Tools

Hadoop

Spark

TensorFlow

PyTorch

MLFlow

Job description

Pinterest is seeking a Machine Learning Engineer to advance large-scale recommender systems and AI-driven experiences. You will tackle challenges across discovery, ads, and search, building and evaluating models to optimize engagement and content recommendations.

The role requires a Master’s in a relevant field, strong ML/NLP/IR skills, experience with big data tools, and proficiency in Python/Java/C++. Collaboration with AI-native engineering is essential in a fast-growing environment.