The Curse of Too-Smart Interviewers

We love training highly intelligent, analytical people on how to become great interviewers. You can see their wheels turning while candidates talk. So much curiosity! Each story provides an endless number of paths to pursue, data points to gather, and follow-up questions to ask. The problem is that there are too many options. Left to…

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Deployment of Exabyte-Backed Big Data Components

Co-authors: Arjun Mohnot, Jenchang Ho, Anthony Quigley, Xing Lin, Anil Alluri, Michael Kuchenbecker   LinkedIn operates one of the world’s largest Apache Hadoop big data clusters. These clusters are the backbone for storing and processing extensive data volumes, empowering us to deliver essential features and services to members, such as personalized recommendations, enhanced search functionality, and…

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A Guide to Recruiting Gen Z

3. Offer competitive compensation and benefits Compensation isn’t always the most important consideration when evaluating job opportunities, but it does matter. Gen Z workers are the most likely to feel underpaid: Over half (57%) think they earn less than they deserve. Competitive compensation can help you attract the youngest generation of workers — so long…

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Practical Magic: Improving Productivity and Happiness for Software Development Teams

Co-authors: Max Kanat-Alexander and Grant Jenks Today we are open-sourcing the LinkedIn Developer Productivity & Happiness Framework (DPH Framework) – a collection of documents that describe the systems, processes, metrics, and feedback systems we use to understand our developers and their needs internally at LinkedIn.  Now more than ever, developers are navigating so much change and…

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Enhancing Content Review: Proactively addressing threats with AutoML

Figure 3: This illustration summarizes how the AutoML framework automates the model training, development, and deployment steps  The AutoML framework trains classifiers, experimenting with multiple model architectures in parallel. It performs a systematic search over a range of hyperparameters, optimization approaches, and models, saving data scientists the effort of trying different algorithms manually.  The AutoML…

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