[行動應用程式設計師]Engineer for Video Recommendation Framework,薪資至少:40000,公司:KKBOX－資訊|軟體|網路行業工作薪資年薪行情-JAVA,雲端,CSS,Javascript,HTML,C++,PHP,MySQL,iOS,Android,Angular,Ruby,Rails,NodeJS,Python,ASP.NET

本訊息有效時間:2014-07-06 到 2014-10-04

職務類別	行動應用程式設計師
職務名稱(薪資)	Engineer for Video Recommendation Framework (薪資&年薪可到:40000~...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</span><--全選複製, 再使用解碼器解開(見右上方「解碼器說明」))
公司名稱	KKBOX

工作或公司地點	台北市南港區三重路19-3號一樓 (南港軟體工業園區)
工作內容/職務描述	KKBOX is the leading music streaming company in Asia, possessing millions of music entries to serve users' daily needs. Nevertheless, when confronted with vast amount of songs, it becomes difficult for users to ferret out their desired ones. The mission of Research Team is to dig out a means of organizing millions of songs in all aspects you can imagine, and recommend songs just like the old friend of our users. After shipping the radio service of KKBOX, “Discovery”, we want to start a new journey to explore the recommendation in movie application. When it comes to movie recommendation, the first thing comes to our mind is the well-known Netflix prize, which makes countless engineers work day and night to improve the algorithms by 10%. But mentioning this contest does not mean that we just want to make a clone of it, our goal is to build a world-class recommender system even to compete with Netflix. Therefore, your duty would be playing with real video streaming data and replicate the experiments of Netflix’s contest. Based on the lessons learnt from the Netflix contest, you can work with a bunch of excellent colleagues and design the video recommendation framework from the top down. - Responsibility Ensure that the necessary data logging is in place to tracking the “pleasure” of our user. Implement/refine the video recommender system and give suggestions on how to improve it. Give suggestions to product team on how to use recommender system. - Technique requirement Familiar in scripting languages Python/Perl. Familiar with Git. Familiar with development under Unix system Knowledge in the main directions of recommender systems and the advantages/drawbacks of each one, Ex: user/item based recommendation, content-based recommendation. Knowledge in at least one recommender system in detail. Experiences on implementing one would be a plus. Experience working with large data sets, cloud technologies is a plus. Ex: Hadoop, Pig, Hive, MapReduce.
應徵資訊	Please kindly submit your resume to [email protected] for the application. Thanks.

工作或公司地點

台北市南港區三重路19-3號一樓 (南港軟體工業園區)

工作內容/職務描述

KKBOX is the leading music streaming company in Asia, possessing millions of music entries to serve users' daily needs. Nevertheless, when confronted with vast amount of songs, it becomes difficult for users to ferret out their desired ones. The mission of Research Team is to dig out a means of organizing millions of songs in all aspects you can imagine, and recommend songs just like the old friend of our users. After shipping the radio service of KKBOX, “Discovery”, we want to start a new journey to explore the recommendation in movie application.

When it comes to movie recommendation, the first thing comes to our mind is the well-known Netflix prize, which makes countless engineers work day and night to improve the algorithms by 10%. But mentioning this contest does not mean that we just want to make a clone of it, our goal is to build a world-class recommender system even to compete with Netflix. Therefore, your duty would be playing with real video streaming data and replicate the experiments of Netflix’s contest. Based on the lessons learnt from the Netflix contest, you can work with a bunch of excellent colleagues and design the video recommendation framework from the top down.

- Responsibility

Ensure that the necessary data logging is in place to tracking the “pleasure” of our user.
Implement/refine the video recommender system and give suggestions on how to improve it.
Give suggestions to product team on how to use recommender system.

- Technique requirement

Familiar in scripting languages Python/Perl.
Familiar with Git.
Familiar with development under Unix system
Knowledge in the main directions of recommender systems and the advantages/drawbacks of each one, Ex: user/item based recommendation, content-based recommendation.
Knowledge in at least one recommender system in detail. Experiences on implementing one would be a plus.
Experience working with large data sets, cloud technologies is a plus. Ex: Hadoop, Pig, Hive, MapReduce.

應徵資訊

Please kindly submit your resume to [email protected] for the application. Thanks.

來源網址：http://jobs.inside.com.tw/jobs/4516

本訊息有效時間:2014-07-06 到 2014-10-04