Software Engineer, Machine Learning (PhD University Grad) 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
Currently has or is in the process of obtaining a PhD degree or completing a postdoctoral assignment in the field of Machine Learning or similar
Interpersonal skills: cross-group and cross-culture collaboration
Research and/or work experience in machine learning, NLP, recommendation systems, pattern recognition, signal processing, data mining, artificial intelligence, information retrieval or computer vision.
Experience in systems software or algorithms
Knowledge in Java or C++, Perl, PHP or Python
Problem solving capabilities
Proven track record of achieving results as demonstrated by grants, fellowships, patents, as well as first-authored publications at workshops or conferences such as ICML, NIPS, KDD or similar
Demonstrated software engineer experience via an internship, work experience, coding competitions, or used contributions in open source repositories (e.g. GitHub)
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