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.
- 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)
- 5+ years of experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining or artificial intelligence
- Proven experience 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
About the company
Facebook is an American online social media and social networking service company. 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.