Machine Learning Engineers â€" Integrity and Anti-Abuse

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 â€" we're just getting started.

Facebook is seeking Machine Learning Engineers to join our engineering team. The ideal candidate will have industry experience working on a range of classification, ranking and optimization problems, e.g. payment fraud, abuse detection, click-fraud detection, quality-based ranking, bad actor behavior modeling, adversarial ML, or spam detection. The position will involve taking these skills and applying them to some of the most exciting and massive social data, actor and content understanding problems that exist on the web.


  • Develop situational awareness in a highly adversarial environment and keep Facebook's anti-abuse capabilities ahead of our attackers
  • Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rule-based models
  • Suggest, collect and synthesize requirements and create effective feature roadmap
  • Apply state-of-the-art ML techniques to a broad range of products and use cases
  • Extend state-of-the-art ML on areas such as actor profiling, content understanding (text, image, video, audio, web) as well as new adversarial ML techniques
  • Analyze the latest attacker techniques and apply solutions to detect them holistically and stop them proactively
  • Take a leadership role in driving anti-abuse initiatives across the company
  • MS degree or Ph.D. degree in Computer Science or related quantitative field
  • 3+ years of industry engineering experience in one or more of the following areas: machine learning, anomaly detection, recommendation systems, pattern recognition, data mining, content understanding or artificial intelligence
  • Experience performing data analysis and translating the results 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

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