Software Engineer, 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 Software Engineers experienced in abuse detection to help keep our two billion users safe from negative experiences in a highly adversarial environment. The ideal candidate will have industry experience working and building scalable detection systems on a range of problems that keep spam, fraud, deception, and abuse at bay, and are resistant to adversarial iterations. As a successful candidate, you will bring your passion and experience to designing novel anti-abuse measures and deploying them across Facebook's products. We are looking for someone who loves reimagining what's possible when it comes to detecting and disrupting attackers, and building software to realize those ideas to make the internet a safer place for all. This position is full-time and based in our Menlo Park, CA office.
- Develop situational awareness in a highly adversarial environment and keep Facebook's anti-abuse capabilities ahead of our attackers.
- Build highly scalable classifiers and tools leveraging machine learning and rule-based models.
- 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.
- Collaborate with Facebook's leading Machine Learning & Artificial Intelligence teams and apply their innovations to fighting abuse.
- B.S. or M.S. in Computer Science or related field, or equivalent experience
- 3+ years of engineering experience in one or more of the following areas: abuse, spam or fraud detection, trust & safety
- Proven ability to perform rigorous data analysis and translate the results into business recommendations.
- Experience with programming and/or scripting languages such Java, C++, Perl, Python, PHP.
- Contributions to the security community (open source, public research, blogging, presentations, etc.).
- Ph.D. degree in Computer Science or related quantitative field.
- Experience working with large datasets, using tools such as Hadoop/Hive/HBase/Pig or MapReduce/Sawzall/Bigtable.
- Experience with anomaly detection, machine learning, recommendation systems, pattern recognition, data mining, content understanding, or artificial intelligence.
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