High Scalability

MARCH 24, 2020

Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). You will be designing and implementing distributed systems : large-scale web crawling platform, integrating Deep Learning based web data extraction components, working on queue algorithms, large datasets, creating a development platform for other company departments, etc.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

MAY 26, 2020

has hours of system design content. They also do live system design discussions every week. Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! Created by former senior-level AWS engineers of 15 years. Who's Hiring? Apply here.

Education 100

Education AWS Software Engineering Scalability 100

High Scalability

MARCH 30, 2020

has hours of system design content. They also do live system design discussions every week. Scrapinghub is hiring a Senior Software Engineer (Big Data/AI). this is going to be a challenging journey for any backend engineer! How to screen candidates efficiently, effectively, and without bias. Who's Hiring?

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

MARCH 17, 2020

Sisu Data is looking for machine learning engineers who are eager to deliver their features end-to-end, from Jupyter notebook to production, and provide actionable insights to businesses based on their first-party, streaming, and structured relational data. How to screen candidates efficiently, effectively, and without bias.

Education 105

Education Engineering Java Software Engineering 105

High Scalability

MARCH 3, 2020

Sisu Data is looking for machine learning engineers who are eager to deliver their features end-to-end, from Jupyter notebook to production, and provide actionable insights to businesses based on their first-party, streaming, and structured relational data. How to screen candidates efficiently, effectively, and without bias.

Education 114

Education Games Engineering Java 114

High Scalability

FEBRUARY 18, 2020

Sisu Data is looking for machine learning engineers who are eager to deliver their features end-to-end, from Jupyter notebook to production, and provide actionable insights to businesses based on their first-party, streaming, and structured relational data. How to screen candidates efficiently, effectively, and without bias.

Education 113

Education Games Engineering Java 113

High Scalability

FEBRUARY 9, 2020

Sisu Data is looking for machine learning engineers who are eager to deliver their features end-to-end, from Jupyter notebook to production, and provide actionable insights to businesses based on their first-party, streaming, and structured relational data. How to screen candidates efficiently, effectively, and without bias.

Education 108

Education Games Engineering Java 108

The Morning Paper

APRIL 16, 2019

Teaching rigorous distributed systems with efficient model checking Michael et al., We would like students to consider the performance characteristics of their systems, and our tests check that their designs attain reasonable run-time performance. EuroSys’19. On the surface you might think today’s paper selection an odd pick.

Systems 43

Systems Efficiency Testing Strategy 43

SQL Server According to Bob

JANUARY 24, 2017

Many of you have used WinDbg , Visual Studio or other other debugging utilities but none of these are designed for PE and ELF in the same process space. You can always debug the SQL Server on Linux from assembly but assembly is often too low level for general debugging needs and efficiency. Dump Formats / State Captures.

Servers 40

Servers Open Source Software Engineering Processing 40

SQL Server According to Bob

JUNE 27, 2016

I was contacted by my friend, Slava Oks, to start looking at how Microsoft SQL Server Support (CSS) would support the endeavor, train engineers, run SQL Server on Linux through its paces, find bugs and lend my knowledge to making SQL Server on Linux a world class product. For example, we were designing how to capture a crash dump.

Servers 40

Servers Games Azure Software Engineering 40

The Netflix TechBlog

APRIL 26, 2022

We built Axion primarily to remove any training-serving skew and make offline experimentation faster. We will share how its design has evolved over the years and the lessons learned while building it. To understand Axion’s design, we need to know the various components that interact with it.

Storage 187

Storage Design Scalability Latency 187

The Netflix TechBlog

NOVEMBER 20, 2023

It also improves the engineering productivity by simplifying the existing pipelines and unlocking the new patterns. We will show how we are building a clean and efficient incremental processing solution (IPS) by using Netflix Maestro and Apache Iceberg. Introduction Netflix relies on data to power its business in all phases.

Processing 210

Processing Big Data Efficiency Engineering 210

O'Reilly

OCTOBER 19, 2021

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. The new category is often called MLOps. This approach is not novel.

DevOps 138

DevOps Software Engineering Infrastructure Open Source 138

The Netflix TechBlog

OCTOBER 18, 2022

These include ETL pipelines, ML model training workflows, batch jobs, etc. Similarly, ML model training workflows usually consist of tens of thousands of training jobs within a single workflow. Maestro engine service will deduplicate the triggering requests to achieve an exact-once guarantee when scheduling workflows.

Java 202

Java Scalability Traffic Architecture 202

O'Reilly

MAY 19, 2020

Live online training, videos, books, certification prep, and more, from O’Reilly and our partner publishers. More than one-third have adopted site reliability engineering (SRE); slightly less have developed production AI services. Designing a survey inevitably entails making a spate of methodological trade-offs.

Cloud 141

Cloud Serverless AWS Architecture 141