Machine Learning Researchers build production grade machine learning algorithms that operate in real time or at scale. Researchers are responsible for applying, adapting, and extending existing results in the broad field of machine learning, while also conducting novel research as required. We are interested in all aspects of ML including: predictive modelling, clustering, time series analysis, natural language processing, and computer vision. Successful researchers manage all aspects of the research process including methodology selection, data collection and analysis, implementation and testing, prototyping, and performance evaluation.
• Strong understanding of statistical analysis and computational modelling.
• Strong understanding of algorithms and data structures.
• Familiar with map reduce and big data processing (Spark, Hadoop, DataFlow, etc).
• TensorFlow (or another GPU integrated deep learning library).
• Deep understanding of machine learning algorithms.
• Deep understanding of numerical optimization.
• Strong understanding of data structures and algorithms.
Plus, but not required:
• Previous experience in tech industry (GOOG, AMZN, FB, NFLX, Spotify, etc).
• Experience building industrial grade ETL pipelines.
• Experience building frontend systems.
• Familiarity with dashboards and other visualization tools.
• Ability to derive generalization bounds for common ML algorithms.
• Experience developing new machine learning algorithms.