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In this role, you will build production-grade machine learning models to serve best-in-class shopping and delivery experience to millions of customers on Amazon. This requires you to formulate ambiguous business problems into solvable scientific problems, work with large-scale data pipelines, perform extensive data cleaning and exploration, train and evaluate your models in a robust manner, design and conduct live experiments to validate model performance, and automate model inference on AWS infrastructure.
Key job responsibilities- Build large-scale data pipelines for training and evaluating the models using PySpark/SparkSQL
- Extensively clean and explore the datasets
- Train and evaluate ML models in a robust manner
- Design and conduct live experiments to validate model performance
- Automate model inference and monitoring and on AWS infrastructureTokyo, 13, JPN
- PhD, or Master's degree and 5+ years of applied research experience
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Strong understanding of statistical analysis (hypothesis testing and experiment design) and machine learning techniques for tabular data
- Experience in developing and implementing machine learning models for tabular data in production
- Publications in top-tier machine learning conferences
The salary information can be provided individually prior to the 1st interview
賃金に関する条件は、1次面接の前に個別にご案内することができます
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