Glassdoor Engineering

Building and Scaling Glassdoor’s ML Platform and Engineering team and the lessons learnt.

Improvements on our text embedding based approach for Fishbowl recommendations

A YAML based approach for building data processing pipelines

Our approach of implementing MLOps to streamline the life cycle of ML projects and increase our productivity

Glassdoor recently acquired Fishbowl, a professional networking community where working professionals can have workplace related…

Learn how Glassdoor performs data ingestions from APIs at scale

Interdisciplinary analytics projects a pain? Glassdoor Decision Science has tips for insights generation for cross-functional stakeholders.

Here at Glassdoor we take UI testing seriously, but the main focus has been on end-to-end (E2E) integration tests as opposed to small…

What is needed to be an awesome Software Development Engineer in Test? Here are 5 keys that have helped me find success!

Using Apache Taurus for performance testing your application

Comprehensive performance tuning settings for Datastax’s Java based Cassandra client

How we designed and built a production-scale close-to-real-time system to improve search relevance at Glassdoor

As we continue to tackle tech challenges, we plan to share some of our learnings with the tech community through our engineering blog

Breaking down how we built a production-scale nearline system to improve search relevance at Glassdoor

What is Reactive programming?

Discovering changes in search intent for tech job queries over time

We designed and implemented our very own flexible, reliable, and easy to use experimentation suite

Glassdoor’s GraphQL Journey with Apollo Federation and GraphQL manager