Facebook is seeking Lead/Senior machine learning engineers to join our engineering team. They will have industry experience working on a range of classification, recommendation and searching problems, e.g. issue detection, recommendation systems, search ranking, flow optimization. The position will involve taking these skills and applying them to build a solution system to help businesses on Facebook to address issues with using our product. They will bring the ability to own the whole Machine Learning life cycle, define strategy and projects, and drive excellence across teams.
Software Engineer, Machine Learning Responsibilities
Consistently advance the state of Machine Learning for your problem, including setting and executing against roadmaps for 6-month+ timeframes and influencing business and product strategy.
Define projects for other engineers to solve and achieve impact based on your direction.
Own the full Machine Learning life cycle (https://research.fb.com/the-facebook-field-guide-to-machine-learning-video-series/) for a significant new product, including production quality.
Code deliverables in tandem with the engineering team
PHD in Computer Science with 3+ years or Masters in Computer Science with 7+ 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/Hive/Spark
Expert knowledge in building and training machine learning models or developing production level Machine Learning products in Java, C++ or Python
Expert with scripting languages such as Python, Perl, PHP, and/or shell scripts
Experience developing and debugging in Java, C++ or similar
Experience of demonstrating technical leadership working with teams, owning projects, defining and setting technical direction for projects.
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