Facebook Software Engineer, Media Ranking in Seattle, Washington
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 Media Ranking engineering team. Sharing and consumption of rich media such as Video, Live, 360 and Instant Articles is a very fast growing and exciting facet of all Facebook applications. The Media division at Facebook is working on revolutionizing how people create, distribute and consume video content. The Media Ranking team is at the forefront of accelerating the adoption of all media centric experiences. The vision for the team is to rank and recommend rich media content to our community across various applications and devices, greatly increasing adoption and engagement. The team would be responsible for building multiple ranking and recommendation solutions that optimize for different device form factors (from mobile phones TV), for different markets and different media types (VoD, Live, 360). The ideal candidate will have industry experience working on a range of classification problems, ranking, regression, clustering, natural language processing (query understanding, document understanding), ranking and recommendation systems.
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)
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
- Experience with filesystems, server architectures, and distributed systems
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