Software Engineer, Pages Science

(Seattle, WA)

Facebook's mission is to give people the power to build community and bring the world closer together. Through our family of apps and services, we're building a different kind of company that connects billions of people around the world, gives them ways to share what matters most to them, and helps bring people closer together. Whether we're creating new products or helping a small business expand its reach, people at Facebook are builders at heart. Our global teams are constantly iterating, solving problems, and working together to empower people around the world to build community and connect in meaningful ways. Together, we can help people build stronger communities — we're just getting started.

Facebook is seeking Machine Learning Engineers to join our Pages Science engineering team. This team helps people stay connected to their interests, and Pages find their audience. Our work is at the intersection of behavioral science, social network analysis, and machine learning. We support the local presence of Pages across Facebook, including recommender systems, feed, and search. We also work to help page admins best promote their interests effectively, through automatic content curation and ad delivery.The ideal candidate will have industry experience working on a range of classification and optimization problems, online embeddings, online co-interaction monitoring, recommender systems, control systems, collaborative filtering, content filtering, and deep learning. 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)

Minimum Qualifications

  • MS degree in Computer Science or related quantitative field or Ph.D degree in Computer Science or related quantitative field
  • 5+ years of experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining or artificial intelligence
  • Proven ability to translate insights into business recommendations
  • Experience with Hadoop/Hbase/Pig or MapReduce/Sawzall/Bigtable
  • Knowledge developing and debugging in C/C++ and Java
  • Experience with scripting languages such as Perl, Python, PHP, and shell scripts

Preferred Qualifications

  • Experience with filesystems, server architectures, and distributed systems

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