Facebook Software Engineer, Machine Learning in London, United Kingdom
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 engineering team. The ideal person will have industry experience working on a range of classification and optimisation 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.
Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules based models
Suggest, collect and synthesise 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)
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
Expert knowledge developing and debugging in C/C++ and Java
Experience with scripting languages such as Perl, Python, PHP, and shell scripts
MS degree in Computer Science or related quantitative field with 5+ years of machine learning related work or research, or PhD degree in Computer Science or related quantitative field
Experience with filesystems, server architectures and distributed systems