Snorkel Ai Machine Learning Engineer Interview Guide

About Snorkel AI

At Snorkel AI, we’re redefining how people and organizations build AI applications. Snorkel began as a research initiative in the Stanford AI Lab in 2016, pioneering the approach of programmatically labeled and managed training data. Today, Snorkel Flow, our AI data development platform, empowers some of the largest and most advanced tech organizations in the world, as well as scientists, doctors, and journalists, to build custom AI applications quickly and effectively. Our mission is to democratize AI, making it accessible to everyone.

What We're Looking For

• Expertise in modern machine learning frameworks and technologies
• Significant professional experience with machine learning
• Strong communication skills and ability to work in dynamic environments
• Experience working directly with external customers on ML models

Interview Process

1. Application Review
2. Initial Phone Screen
3. Technical Interview(s)
4. On-site/Virtual Interviews
5. Final Discussions and Offer

What You'll Find in the Guide

Role Expectations

Sample Questions

Tips and Tricks

Company Culture Insights

Preparing for the Technical Interview

Typically, interviews at Snorkel Ai vary by role and team, but commonly Machine Learning Engineer interviews follow a fairly standardized process across these question topics.

We've gathered this data from parsing thousands of interview experiences sourced from members.

Practice for the Snorkel Ai Machine Learning Engineer interview with these recently asked interview questions.