James Long 
[address withheld]
San Jose, CA 95148

Home : [email for more information] 
Cell : [email for more information] 
Email: jamlong [at] gmail [dot] com

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OBJECTIVE

I am currently open to hear about external opportunities. My interests are
largely related to abuse problems (Spam, Policy Abuse, Payment Fraud). 
Specifically, I tend to work on Machine Learning problems where there is so
little data that semi-supervised or unsupervised approaches tend to be
necessary.

More generally: I enjoying transforming data into money through machine
learning.

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EMPLOYMENT HISTORY

January 2017 - Present
Staff Software Engineer - Google - Common Abuse Tools

  Working on Applied Research in the area of Abuse Prevention.

  Similarity -
  Working on a end to end pipeline to do general similarity, utilizing
  Triplet Loss and Quadruplet Loss. Simplifying the process so the user can
  simply provide their dataset, and an embedding model for a single instance,
  and creating a full Triplet Loss model (including optional auxillary tasks
  such as Image Rotation, Autoencoders, etc.). 

  KerasTuner - 
      https://elie.net/talk/cutting-edge-tensorflow-keras-tuner-hypertuning-for-humans/
  Early adopter. Assisted greatly in the refactoring and production readiness
  of KerasTuner.
     https://github.com/keras-team/keras-tuner

  SCAAML - 
  Automated the running of tens of thousands of experiments on Side Channel
  Attacks against crypto keys.

  Re-wrote and open-sourced parts of the SCAAML codebase:
     https://github.com/google/scaaml

  Created an End-to-end Attack Colab/Jupyter notebook:
     https://colab.research.google.com/drive/1VmqDxgvUltgDAvyc1RKGUdJS9Cn6U4GV


June 2016 - December 2016
Staff Software Engineer - Google - Youtube Enforcement

  Planning the future of Youtube Enforcement across Engagement Abuse, Video 
  Abuse, and Content Spam, eliminating redundancy and improving our overall
  Abuse efforts.

  Creating signals and models to detect Spam in Youtube.

  Strategy / C++ / Distributed Systems / Decision Trees / AdaBoost / SVMs
  Data Analysis / SQL
  
January 2014 - June 2016
Staff Software Engineer - Google Research
Freud - Machine Learning Platform - Latent Dirichlet Allocation

  Productionized a distributed implementation of Latent Dirichlet Allocation,
  an algorithm for generate Topic Models, and ran models at massive scale,
  stretching our capabilities (x,xxx machines, xx,xxx CPUs, xxx TB RAM) Paper
  published in OSDI '14 - http://goo.gl/6wUmZY

  Identified potential users, pitched how we could help them, and consulted with
  interested teams across Google (Youtube, Search, News, GMail, Health, and
  others).

  Generated LDA models based on user search data, and launched changes in Search
  Ads, netting a whopping total of $0.X Billion / year in incremental revenue.
    
  C++ / SOA / Distributed Systems / Flume / Machine Learning / LDA / Research

November 2011 - January 2014
Staff Software Engineer - Google - Payment Fraud

  Tech Lead for Risk Infrastructure (7 developers), owning the infrastructure
  used to detect fraud and abuse in all paid Google products (AdWords, Checkout,
  Pay By Gmail, Enterprise, etc.) 
 
  Lead a major project (~2 years, 3 engineers) to build a custom database and
  query engine tailored to our teams needs. Final system handles
  350,000 read QPS and 100,000 update QPS, while reducing latency of our signal
  collection by 98%, and turning down 3 legacy systems used for similar signals.
  Massive productivity gains for ~30 engineers working on signals.

  Owned the first models for detecting policy abuse in AdWords (scams,
  counterfeit goods, etc.), leading to a 10x increase in the number of accounts
  (correctly!) shut down for policy violations over what human reviewers were
  able to do.

  Created the first models for detecting Account Take Over (ATO) through
  phishing / malware, reducing fraud losses by ~$24M/year.

  Created a system for automatically detecting duplicate/related customers,
  allowing a single detected abuser to potentially cascade into a large number
  of account suspensions.
	
  Java / Bigtable / MapReduce / Flume / Distributed Systems / SOA
  Machine Learning / SVMs / Decision Trees and Forests / Signals
  Technical Leadership (~7 engineers)

February 2007 - November 2008
Site Reliability / Software Engineer III - Google - Apps for your Domain

  Tech Lead for Apps for Your Domain (now GSuite) - Site Reliability.
  Troubleshoot, improve, and handle on-call for teams like GMail, Apps
  for Your Domain, and Google's authentication service.

  Troubleshooting / Load Balancing / Site Reliability
  Technical Leadership (~6 engineers)

July 2002 - January 2007
Software Developer II - Amazon.com - Personalization

  Automated our flagship marketing e-mail campaign, reducing the number
  of humans needed by 10+, while expanding the number of products we
  could promote. Fully automated e-mail campaigns generated ~$1M in yearly
  revenue.

  Maintained production environment, including specialized hardware for sending
  transactional and merchandising e-mail.

  Lead several small team (2-3 engineer) projects.

  C++ / Java / SOA / Perl / Oracle / MySql / Recommendations / SMTP
  Team Leadership (~3 engineers)

August 2001 - May 2002 
Freelance Developer - NetMath at the University of Illinois - Urbana-Champaign
  
  Created a virtual classroom / homework hand-in system, which was used for
  more than a decade.

  PHP / MySQL / HTML 

Summer 2001 
Software Development Intern - Microsoft 
Media Player

  Created a JNI based plugin for Windows Media Player (to allow embedding
  in Netscape without licensing issues.

  Java / JNI / C++ / Javascript

Summer 2000 
Software Development Intern - Microsoft 
Learning Technologies Group

  Created a prototype of an online classroom, with streaming video/audio, 
  user-driven questions, polls, notes, and more.  

  HTML / Javascript / COM

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EDUCATION

1998 - 2002 University of Illinois at Urbana-Champaign
Bachelor of Science - Computer Science
James Scholar (http://jamesscholar.cen.uiuc.edu/) 

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REFERENCES

Available upon request.