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

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! Learn how to train interviewers so everyone's on the same page. Who's Hiring?

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

The Morning Paper

FEBRUARY 18, 2020

The key insight this led to is that ML models are software , derived from data. ML learning systems combine the characteristics of software, e.g. the need for CI/CD pipelines, and of data, e.g. the need to track lineage. Many of the software engineering discipline and controls need to be brought over into an ML context.

Government 95

Government Software Engineering Storage Database 95

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. Learn how to train interviewers so everyone's on the same page. Apply here.

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. Learn how to train interviewers so everyone's on the same page. Apply here.

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. Learn how to train interviewers so everyone's on the same page. Apply here.

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. Learn how to train interviewers so everyone's on the same page. Apply here.

Education 108

Education Games Engineering Java 108

O'Reilly

NOVEMBER 12, 2019

Respondents who have implemented serverless made custom tooling the top tool choice—implying that vendors’ tools may not fully address what organizations need to deploy and manage a serverless infrastructure. As noted earlier, the majority of survey respondents are software engineers. Industries of survey respondents.

Serverless 88

Serverless Architecture FinTech Infrastructure 88

Adrian Cockcroft

FEBRUARY 13, 2023

Discussion of the water positive goal and optimizations that let AWS return water directly for irrigation rather than to the sewage system. Provides comparison of inference workload on P4dn GPU instances vs. AWS Trainium saving 92% energy and 90% cost, and training workload on P4dn vs. AWS Inferentia 2.6x

AWS 64

AWS Energy Architecture Programming 64

All Things Distributed

SEPTEMBER 4, 2017

And thirdly, an "algorithmic revolution" has taken place, meaning it is now possible to train trillions of algorithms simultaneously, making the whole machine learning process much faster. For the past 20 years, thousands of software engineers at Amazon have been working on ML. Machine Leaning at Amazon.

Artificial Intelligence 147

Artificial Intelligence Transportation Education Airlines 147

Brendan Gregg

APRIL 30, 2018

USENIX’s LISA conference is the premier event for topics in production system engineering. We both have had long careers supporting system administration, and LISA has always felt like a homecoming, reuniting with old friends while welcoming newcomers. Submit #lisa18 talk, training, panel, and demo proposals by May 24 [link].

DevOps 43

DevOps Network Best Practices Programming 43

Brendan Gregg

APRIL 29, 2018

USENIX’s LISA conference is the premier event for topics in production system engineering. We both have had long careers supporting system administration, and LISA has always felt like a homecoming, reuniting with old friends while welcoming newcomers. Submit #lisa18 talk, training, panel, and demo proposals by May 24 [link].

DevOps 40

DevOps Network Best Practices Programming 40

O'Reilly

OCTOBER 19, 2021

As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. In effect, the engineer designs and builds the world wherein the software operates. The new category is often called MLOps. Why did something break?

DevOps 138

DevOps Software Engineering Infrastructure Open Source 138

The Netflix TechBlog

APRIL 26, 2022

We built Axion primarily to remove any training-serving skew and make offline experimentation faster. We make sure there is no training/serving skew by using the same data and the code for online and offline feature generation. Our machine learning models train on several weeks of data.

Storage 187

Storage Design Scalability Latency 187

The Netflix TechBlog

OCTOBER 16, 2019

Without infrastructure-level support, every team ends up building their own point solution to varying degrees of success. Dataset propagation At Netflix we use an in-house dataset pub/sub system called Gutenberg. for example to train machine-learned models. Gutenberg allows for propagating versioned datasets ?—?consumers

Cache 187

Cache Architecture Metrics Java 187

O'Reilly

MAY 19, 2020

Live online training, videos, books, certification prep, and more, from O’Reilly and our partner publishers. O’Reilly Learning > We wanted to discover what our readers were doing with cloud, microservices, and other critical infrastructure and operations technologies. Respondent Demographics.

Cloud 141

Cloud Serverless AWS Architecture 141