Careers at Facebook

Software Engineering

Software Engineer, Machine Learning

Vị tríMenlo Park, CA
Facebook was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at Facebook offers countless ways to make an impact in a fast growing organization.
Facebook is seeking a machine learning engineer to join our engineering team in Menlo Park. The ideal candidate will have industry experience working on a range of classification and optimization problems, e.g. payment fraud, click-through rate prediction, click-fraud detection, search ranking, text/sentiment classification, collaborative filtering/recommendation, or spam detection. The position will involve taking these skills and applying them to some of the most exciting and massive social data and prediction problems that exist on the web.

Responsibilities

  • Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models
  • Suggest, collect and synthesize requirements and create effective feature roadmap
  • Code deliverables in tandem with the engineering team
  • Adapt standard machine learning methods to best exploit modern parallel environments (e.g. distributed clusters, multicore SMP, and GPU)

Requirements

  • B.S. Computer Science. M.S. or Ph.D. a plus
  • A minimum of 5 or more years experience in one or more of the following areas: Fraud prevention engineering, machine learning, large-scale data mining for analytics.
  • Proven ability to translate insights into business recommendations
  • Experience with Hadoop/Hbase/Pig or Mapreduce/Sawzall/Bigtable a plus
  • Expert knowledge developing and debugging in C/C++ and Java on *nix
  • Experience with scripting languages such as Perl, Python, PHP, and shell scripts
  • Experience with filesystems, server architectures, and distributed systems
EOE Minorities/Females/Protected Veterans/Individuals with a disability.
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