Job Opportunities in Taiwan

關於Quid（Net Base美商網基品牌）

總部位於矽谷，Quid是一家快速成長且充滿創業精神的公司。在全球社群媒體分析平台上，我們處於世界領先地位，達到30%以上的成長！

我們將網際網路上的資訊，如 Facebook 貼文、Instagram圖片、 You Tube留言、Twitter 、各大新聞、消費者評論、產品評論、業務文檔，再到專利申請和論壇等數據，透過匯總、分析並經由最尖端的文字分析技術、自然語言處理技術(Natural Language Processing)及電腦視覺(Computer Vision)分析之後，幫助客戶從數據中取得有價值的資訊，透過我們的工具及服務，客戶可以更快速、更全面地了解市場趨勢、競爭對手、消費者偏好等，能制定更有效的營銷策略和商業決策，從而在市場中佔有更大的優勢。

In this Machine Learning Engineer Intern role, you will work closely with AI R&D team to tackle problems in content discovery, text mining and data analytics, with projects such as:

• Discovering topics of conversation across billions of social media posts
• Identifying and tracking trends
• Enabling user-driven customizations, e.g. with transfer learning
• Correlating natural language data with business metrics
• Building knowledge graph to help customer discover insights

Quid is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

**Responsibilities**

• You are expected to work with our AI engineers to apply scientific thinking and techniques to implement experimental product features
• You will be coding in Python/Java, working on Hadoop/Spark and Kubernetes
• You will build machine learning models through all phases of development, from design through training, evaluation, and implementation in AI system.
• You will be presenting result of experiment to team and product manager
• You will work with team to apply CI/CD in project development

**Requirements**

• At least 6 months commitment, available to work 24 hours per week, and 40 hours per week during summer vacation (WFH is fine). Starting in July 2024.
• BS, MS or Ph.D. in Computer Science or equivalent
• Experience with statistical modeling, machine learning techniques applied to natural language processing
• Practical experience in training model and developing machine learning system
• Good communication and collaboration skills to work with people, passionate to solve challenging problems.

**Nice To Haves**

• Understanding of deep learning algorithms and workflows
• Familiarity with technologies like Tensorflow, Spark MLlib, and Scikit-learn
• Experience with social media data
• Utilizing LLM or grasping some of the LLM principles.