Machine Learning Engineer, Core Engineering

Remote

Quick summary

Work type: Remote
Location: San Francisco, CAWA
Salary: $138,905–$285,982 / yr
Posted: 4 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $220k

This role $212k

$121k most similar roles pay here $304k

This role pays more than 50% of similar roles. Most pay $189,750–$249,750 — the shaded band above. At the midpoint, this role pays about $212k versus about $220k for comparable roles.

Based on 240 similar postings.

Employer

About Pinterest

Pinterest is a visual discovery and inspiration platform where people find ideas for home, style, recipes, and more. It serves hundreds of millions of users worldwide through its image and video pinboard product.

Pinterest currently has 36 open roles on FindRole.

Listed pay typically runs $164,695–$332,012 across 35 roles with salary data.

Most-posted roles

View all roles at Pinterest

At a glance

TL;DR · Machine Learning Engineer, Core Engineering

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As a Senior Machine Learning Engineer at Pinterest, you will join a dynamic and innovative team to develop cutting-edge personalized experiences for over 500 million users. Your daily responsibilities include building advanced technology using deep learning and machine learning techniques to enhance various product surfaces such as Homefeed, Ads, Growth, Shopping, and Search. You will collaborate closely with cross-functional teams to experiment and improve ML models while leveraging Pinterest’s vast data resources to refine candidate retrieval systems. This role requires hands-on experience in constructing large-scale data processing pipelines and big data technologies like Hadoop/Spark, along with a strong background in machine learning methods such as user modeling, personalization, and recommender systems. Ideal candidates possess a Bachelor's degree in computer science or related fields and have expertise in scalable real-time systems for stream data processing.

Skills

Python Spark Hadoop TensorFlow PyTorch Kafka Redis PostgreSQL CI/CD Docker AWS Scikit-learn Pandas Numpy Jupyter Git Bash SQL

What you'll do

Build personalized experiences using deep learning and machine learning technologies.
Improve ML models for Homefeed, Ads, Growth, Shopping, and Search products.
Enhance candidate retrieval through data-driven methods and unique data properties.
Experiment rapidly in a high-impact environment with quick product launches.
Stay updated on industry trends in recommendation systems.

What we're looking for

2+ years of industry experience applying machine learning methods like user modeling and recommender systems.
Hands-on experience building data processing pipelines and large-scale ML systems using big data technologies.
Bachelor’s degree in computer science, machine learning, statistics, or a related field.
Expertise in scalable real-time systems that process stream data (nice to have).
Passion for applied machine learning and the Pinterest product (nice to have).
Experience with Hadoop/Spark and other big data technologies.

Hybrid

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