Software Engineer, Business Integrity Optimization
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 Business Integrity Optimization engineering team. This team applies advanced feature generation and machine learning models to help make sure only high quality content created by advertisers, page owners, merchants, etc. are delivered to our users in order to ensure a satisfactory and sustainable experience. This team creates and improves hundreds of production Machine Learning (ML) models to ensure scalability of our content review process and minimizes the amount of negative experiences within Ads, Pages, Marketplace, Groups, Messenger, etc. on Facebook, by automatically detecting policy violation and low quality content. Business Integrity Optimization offers the unique challenge of dealing with a large variety of ML problems (classification, regression, ranking) applied to different type of components (e.g., text, video, image, URL) and the unique opportunity of combining it with human computation within our ML workflows.The ideal candidate will have industry experience working on a range of classification problems, deep learning, content understanding and natural language processing, penalty and ranking features.
- 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
Meet Some of Facebook's Employees
Manager, Global Client Solutions
Peipei helps Facebook’s top clients devise solution-based and results-driven social media strategies. She creates strategic partnerships to help people and brands connect in a more meaningful way.
Back to top