| 求才職稱 | 資格條件 | 工作內容 | 待遇 | 工作地點 | 需求人數 |
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Algorithm Engineer
(理工科系職缺：是)
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Skill Requirements: ● 1+ years developing high quality software in Java or equivalent Object- Oriented language.
● Experience in building and optimizing ‘Big Data’ data pipelines, architectures and data sets.
● Experience working with large datasets, using tools like Hadoop, Spark, Kafka, HBase, etc.
● Better understanding about SQL and NoSQL
● Strongly self-motivated and self-driven, a good team player
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Taboola, the world’s largest content recommendation platform, is hiring an algorithm engineer to join our R&D Team in Taiwan. ● Implement Big Data machine learning pipelines;
● Analyze Big Data to find patterns and features to be used in machine learning models;
● Research, design, build and validate machine learning models based on business use cases and KPI given;
● Implement online experiments to evaluate and refine machine learning models;
● Productize machine learning models and implement optimization algorithms based on the models;
● Other machine learning and data science related work.
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月薪：100000 - 150000
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臺北市
信義區基隆路一段206號19樓
| 2 |
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Algorithm Engineer Intern
(理工科系職缺：是)
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※Able to work full-time for at least 3 months
●1 year of full time work experience or 3 months internship experience (only applicable to fresh graduates) in data science is required
●SQL & database experience is preferred
●Experience in collecting data from and loading data to a database or web services is preferred
●Minimum experience in using popular machine learning frameworks, such as PyTorch and Tensorflow
●Good communication skills and ability to explain data and analysis to a variety of audiences and key stakeholders
●Good analytical skills to understand and interpret the data for machine learning
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In this role you will: ●Research and propose data science solutions based on given requirements.
●Research and build content understanding and/or predictive customer behavior models for targeting and personalization.
●Research and implement effective optimization algorithms to achieve certain business goals.
●Present findings to the product team and technical team leads in a clear and actionable way.
●Productize models and algorithms, and deploy them to the production environment.
●Build and support data pipelines for machine learning data preparation.
●Build and support machine learning automation pipelines.
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面議
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臺北市
信義區基隆路一段206號19樓
| 2 |