H2O is the premier open-source machine learning platform that is transforming how machine-intelligence applications are built. With H2O, data scientists can take both simple and sophisticated models to production from the same interactive platform they use for modeling, at enterprise scales. Our customers have built powerful domaterin-specific predictive engines for recommendation, pricing, and outlier detection in fraud & insurance. The H2O.ai team is a mix of Software, Math, and Data Science people working together with the open source community to build H2O.
Responsible for key software system components such as networking and remote procedural call (rpc) handling, distributed exceptions, data compression, and memory management; design and implement parallel distributed inhale and parsing of input data in csv or svmlight format from several possible sources (i.e., nfs, hdfs, S3); design and implement distributed generalized linear modeling algorithm with elastic net regularization and efficient computation of the full regularization path.
Master’s degree (or foreign equivalent) in Computer Engineering, Computer Science, Electrical Engineering, or related field, plus two (2) years of experience in job offered, Software Engineer, Research Assistant or related occupation.
Skills and abilities:
Academic training or work experience must include: Two (2) years of experience with Java and system programming; two (2) years of experience with algorithm design and machine learning tools.