The Netflix TechBlog
JULY 15, 2021
Data Engineers of Netflix?—?Interview Interview with Kevin Wylie This post is part of our “Data Engineers of Netflix” series, where our very own data engineers talk about their journeys to Data Engineering @ Netflix. Kevin, what drew you to data engineering?
O'Reilly
FEBRUARY 18, 2020
It’s the single most popular programming language on O’Reilly, and it accounts for 10% of all usage. This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. In programming, Python is preeminent. Figure 3 (above).
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Dynatrace
JULY 6, 2022
While automating IT practices can save administrators a lot of time, without AIOps, the system is only as intelligent as the humans who program it. This requires significant data engineering efforts, as well as work to build machine-learning models. Monitoring automation is ongoing.
The Netflix TechBlog
MARCH 2, 2021
At Netflix, our data scientists span many areas of technical specialization, including experimentation, causal inference, machine learning, NLP, modeling, and optimization. Together with data analytics and data engineering, we comprise the larger, centralized Data Science and Engineering group.
The Netflix TechBlog
NOVEMBER 22, 2019
4pm-5pm OPN 303-R BPF Performance Analysis Brendan Gregg , Senior Performance Engineer Abstract : Extended BPF (eBPF) is an open-source Linux technology that powers a whole new class of software: mini programs that run on events. We share everything attendees need to implement CloudTrail in their own organizations.
The Netflix TechBlog
JUNE 6, 2022
This will be our “Appsec Reviews and Assessments” function and we are hiring for passionate, early career Appsec engineers to join this group. We will continue to learn as we go through this next phase of evolution of our program. Our focus has been on improving overall security assurance as opposed to just vulnerability prevention.
O'Reilly
SEPTEMBER 15, 2021
64% of the respondents took part in training or obtained certifications in the past year, and 31% reported spending over 100 hours in training programs, ranging from formal graduate degrees to reading blog posts. To nobody’s surprise, our survey showed that data science and AI professionals are mostly male. Salaries by Gender.
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