Mountain View, CA

About Google Engineering

Google is and always will be an engineering company. We hire people with a broad set of technical skills who are ready to tackle some of technology’s greatest challenges and make an impact on millions, if not billions, of users. At Google, software, hardware, network, test and site reliability engineers not only revolutionize search, they routinely work on massive scalability and storage solutions, large-scale applications and entirely new platforms for developers around the world. From AdWords to Chrome, Android to YouTube, Social to Local, Google engineers and designers are changing the world one technological advance after another.

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Apache Beam and Google Cloud Dataflow

Reuven will cover the Beam programming model, and the advantages of hosted Google Cloud Dataflow.

Reuven has been a Google engineering since 2006. In that time, he's been instrumental in building Google's streaming data-processing systems from MillWheel to Cloud Dataflow.

This talk was given at the NYC Data Engineering meetup in June 2016.

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Experiments in a Data-Rich, Information-Poor World

Scalable web technology has greatly reduced the marginal cost of serving users. Thus, an individual business today may support a very large user base. With so much data, one might imagine that it is easy to obtain statistical significance in live experiments. However, this is always not the case. Often, the very business models enabled by the web require answers for which our data is information poor.

In this talk, Amir Najmi from Google will use a simple mathematical framework to discuss how experiment sizing interacts with the business model of some large-scale online services.

Amir Najmi is Principal Quantitative Analyst at Google. He received a PhD in Electrical Engineering from Stanford University under Robert Gray and Richard Olshen. Amir works on statistical modeling and prediction methodology for large-scale high-dimensional data. He is interested in a critical understanding of mathematical models, and the role of human insight in machine learning.

This talk was given at the SF Data Engineering meetup in May 2016.

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Building an ETL Pipeline from Scratch in 30 Mins

This talk shows how to build an ETL pipeline using Google Cloud Dataflow/Apache Beam that ingests textual data into a BigQuery table. Google engineer Silviu Calinoiu gives a live coding demo and discusses concepts as he codes. You don't need any previous background with big data frameworks, although people familiar with Spark or Flink will see some similar concepts. Because of the way the framework operates the same code can be used to scale from GB files to TB files easily.

This talk was given as a joint event from SF Data Engineering and SF Data Science.

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GopherFest 2015: Andrew Gerrand on the Current State of Go.

In this talk Andrew Gerrand discusses the state of Go; what's happening in the Go core in the lead up to Go 1.5.

Full list of all GopherFest 2015 videos here

Among the major changes are the conversion of the tool chain from C to Go, a new concurrent garbage collector, new tools for tracing and program analysis, and support for Go on Android and iOS.

More in the video:

This video was recorded at the GoSF meetup at New Relic.

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The State of Go

Andrew Gerrand is an engineer at Google that works on GoLang. In his Gopher SummerFest talk, he takes us through Go’s timeline - where the language was yesterday, where it is today, and what is planned for the future (including the history of the Gopher logo and plans for Go 1.4!).


This talk was given at GoSF: Gopher Summerfest hosted by Google.

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Aysylu Greenberg on "One VM to Rule Them All"

Watch Aysylu Greenberg, Software Engineer at Google and maintainer of the Clojure library Loom, speak on the paper "One VM to Rule Them All" by Thomas Wuerthinger, Christian Wimmer, et al.


The paper explains how you can write an interpreter and get an optimizing just-in-time (JIT) compiler for free. This enables language designers to focus on features without worrying about the complexities of compiler optimizations and code generation. This paper presents a Java Virtual Machine (JVM) that allows the application to control the JIT compiler behavior at runtime. Aysylu discusses how various programming languages can take advantage of this framework.

To intrigue compiler aficionados, the authors show how combining AST node rewriting during interpretation, optimization, and deoptimization produces high performance code from the interpreter without a language-specific compiler. In addition, they present how features of a variety of programming languages, such as JavaScript, Ruby, Python, R and others, map on the framework.

Check out Aysylu's slides:

This talk was presented at June's edition of Papers We Love hosted by Viggle in NYC.

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Learning Programming - Peter Norvig

Peter Norvig (Engineering Director, Google) speaks about programming education, focusing on University sponsored courses such as Harvard and MIT's EdX online courses, Udacity and other online educational programs.

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The Go Programming Language by Brad Fitzpatrick

This talk is by Brad Fitzpatrick , Staff Software Engineer at Google. It is one of the series of tech talks hosted and sponsored by Airbnb .

Brad will give a tech talk on Go, a new general-purpose programming language developed at and in use by Google, with contributions from nearly 300 open source contributors.

Go gives you the fun and agility of scripting languages, the performance of traditionally-tedious statically typed languages, and built-in language concurrency mechanisms to let you write simple and straight-forward code whether it's small "scripts" or huge servers dealing with millions of action connections, without the pain of either event-based code or the pain of threads.


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