-
-
Save jimhorng/47cc423f4403da4b0d3db86ef9a192a4 to your computer and use it in GitHub Desktop.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Please let me know if you or your friends are interested in this position, thanks :) | |
✔ Company: Digital River https://www.104.com.tw/jobbank/custjob/index.php?r=cust&j=384a426d3c463f6952583a1d1d1d1d5f2443a363189j56 | |
✔ Title: Principal Software Engineer | |
✔ Mission: | |
Build End-to-End Large-scale Machine Learning Systems for improving value proposition for E-commerce. e.g. Increase payment success rate, Fraud detection, Resource utilizations | |
✔ Package: Negotiable, can up to 2-2.5M | |
✔ Requirement: | |
Machine Learning | |
* Machine learning domain knowledge—bias-variance tradeoff, exploration/exploitation—and understanding of various model families, including neural net, decision trees, bayesian models, instance-based learning, association learning, and deep learning algorithms. Hands on experience on adapting common families of models, feature engineering, feature selection and other practical machine learning issues, such as overfitting. | |
* Experience using machine learning libraries or platforms, including :, Caffe, Theanos, Scikit-Learn,or ML Lib for production or commercial products | |
* Experience with building end-to-end machine learning systems | |
* Track record of diving into data to discover hidden patterns and solving operational problems with data science | |
Software Engineering | |
* Solid engineering and coding skills. Ability to write high performance production quality code. Expertise in one or more object-oriented languages,including Python, Go, Java, or C++, and an eagerness to learn more | |
* Experience with building scalable production services | |
Data Engineering | |
* Experience with building and maintaining large scale and/or real-time complex data processing pipelines using Kafka, Hadoop MapReduce, Hive, Storm, Spark, and Zookeeper | |
* Experience in stream processing—Storm, Spark, Flink etc.— and graph processing technologies. | |
* Experience with using data visualization tools (e.g. Tableau, Shiny, d3.js) |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment