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Software Dev Engineer II - Forecasting At Amazon.com

Location: Toronto, Ontario

Job Description

Do you enjoy solving very complex problems with simplest solutions? Are you excited building large-scale distributed systems? Do you enjoy leveraging technology to solve real world problems? Would you like to help us move forward scaling with the cloud and leveraging latest Big Data technologies? We are looking to hire in our Toronto office to work on design, implementation and successful deployment of the next generation Big Data and Machine Learning platform. Our system is mainly focused toward enabling our Forecasting organization to be successful with science experimentation and execution of the mission critical tasks on a daily basis.
You will be building large distributed systems that are reliable, maintainable and scalable. You will get your hands dirty designing full stack of software. You will be optimizing performance through novel approaches to be able to process billion of records in a few seconds! Your software will be used by engineers, scientists and analysts.
We are building a new suite of products aimed at making it easier than ever to experiment and run production data processing systems at petabyte-scale for batch and streaming applications. The suite of products is a complete ecosystem that contains solutions for data handling, Machine Learning model development, automation of the computing resource management, advanced scheduling and orchestration of data processing pipelines, and highly reliable and optimized execution.
Now research scientists, business analysts and application developers have all these technologies and more, integrated together into one coherent infrastructure and available to them with a click of a mouse. They can now concentrate their efforts on solving their business problems, rather than searching for data, maintaining their processing pipelines and debugging compatibility issues or worrying about encryption. Multi-layered architecture provides future proof replaceable components for data storage, highly scalable compute and for model experimentation and evaluation.

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