Responsibilities

  • Develop highly scalable classifiers and tools leveraging machine learning, 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)
  • Perform specific responsibilities which vary by team

Requirements

  • PhD in Computer Science, related STEM or quantitative field
  • Graduating with a PhD by December 2016, or completing a university postdoctoral assignment
  • Research and/or work experience in machine learning, NLP, recommendation systems, pattern recognition, signal processing, large-scale data mining, artificial intelligence, information retrieval or computer vision.
  • Experience in systems software or algorithms
  • Expertise in Java or C++, Perl, PHP or Python
  • Experience with Hadoop/Hbase/Pig or Mapreduce/Sawzall/Bigtable a plus
  • Excellent interpersonal skills, cross-group and cross-culture collaboration
  • High levels of creativity and quick problem solving capabilities
  • Proven track record of achieving significant results
  • PREFERRED: Demonstrated software engineer experience via an internship, work experience, coding competitions, or PhD papers