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. This ML engineer will be tasked with establishing the ML roadmap of projects they are involved in, building ML-based systems, tools and services that are at the core of the project, getting them into production and showing how they bring value to our users. The ideal candidate will have industry experience working on a range of different Machine Learning disciplines, e.g. time series, anomaly detection, recommender systems and others. They will have experience working with large data sets, and will have experience in data-driven decision making. They will also enjoy working with one of the richest data sets in the world, cutting-edge technology and the ability to see your insights turned into real products on a regular basis. They will make a real and meaningful impact on the world. This position is located in our Tel Aviv office.
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 or Ph.D. degree in Computer Science or related quantitative field
Total 8+ years of experience in software engineering, out of which at least 3+ 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
Proficiency in developing and debugging complex software applications
Experience with scripting languages such as Perl, Python, PHP and shell scripts
Experience with filesystems, server architectures and distributed systems
Experience in the domains of recommender systems
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