We are seeking an experienced AI Application Engineer to join our team. The ideal candidate will be skilled in fine-tuning existing models, organizing data, and evaluating the effectiveness of AI applications. The candidate should have a solid foundation in machine learning and be proficient in various AI and data processing tools. Responsibilities: 1. Model Fine-Tuning: • Fine-tune pre-trained models to meet specific application requirements. • Implement transfer learning techniques to adapt models to new tasks. 2. Data Management: • Collect, clean, and organize large datasets for training and evaluation. • Perform data augmentation and preprocessing to improve model performance. 3. Evaluation and Analysis: • Develop metrics and evaluation protocols to assess AI application performance. • Conduct experiments and perform statistical analysis to validate model effectiveness. 4. Deployment and Maintenance: • Deploy AI models into production environments. • Monitor model performance and update models as necessary. 5. Collaboration and Reporting: • Work closely with data scientists, software engineers, and other stakeholders. • Prepare detailed reports and presentations on model performance and project progress. Qualifications: 1. Education: • Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. A Ph.D. is a plus. 2. Technical Skills: • Proficiency in programming languages such as Python or R. • Experience with machine learning frameworks and libraries like TensorFlow, PyTorch, scikit-learn, and Keras. • Familiarity with data manipulation tools such as pandas and NumPy. 3. Experience: • Proven experience in fine-tuning and deploying machine learning models. • Hands-on experience with data preprocessing and augmentation. • Experience in developing and using metrics for model evaluation. 4. Soft Skills: • Strong analytical and problem-solving skills. • Excellent communication and teamwork abilities. • Ability to work independently and manage multiple tasks effectively. 5. Additional Skills: • Knowledge of cloud platforms like AWS, Google Cloud, or Azure is desirable. • Experience with version control systems like Git. • Familiarity with containerization tools such as Docker and Kubernetes is a plus. Preferred Qualifications: 1.Experience in a specific industry (e.g., healthcare, finance, retail) is advantageous. 2.Publications or contributions to the AI community are a plus. Note: 1. Ability to access resource and knowledge in English is extremely essential for the position; as a result, this will be one of the major considerations to the position. 2. An English test will be provided in the interview. 3. [IMPORTANT condition to receive our reply] When the candidate apply the job position, please provide us your summary (both in English and Chinese) of this job description and what you meet the qualifications as well as why you would perform well to the responsibilities, which would be a key factor for the our preliminary assessment for you and the evaluation of the following interview arrangement.

[工作內容] 1.協助關鍵字蒐集、分析、研究與制定使用策略 2.協助SEO數據報表製作與分析 3.追蹤站內外SEO優化策略執行情況與數據記錄 4.協助市場、產業、關鍵字等研究 5.SEO優質文章生產(搭配生成式AI工具使用) 6.協助專案成效為導向的專案管理 [預期職務能力] - 本職務可接受無相關經驗者，預計熟悉崗位工作後應具備以下能力 1.SEO基本知識觀念與優化技能 2.關鍵字分析規劃能力 3.文章優化與生產輸出能力 4.SEO數據分析能力 5.專案進度與成效管理能力 6.生成式AI工具的使用與提示詞優化 [特質要求] - 本職務可接受無相關經驗者，並以內訓培養成中高階專案管理人為發展目標，本項要求為最錄取過程「最優先」考量 1.積極度：對於分配的工作範疇，願以主動尋求資源的心態和行動，讓自己達成對任務的支配能力 2.邏輯力：願意投入思考，對處理任務或問題進行或達成深度的理解和變通 3.同理心：可以以團隊的思考角度，同理同事協作上相互配合的立場，並互相幫助 4.好奇心：對於沒接觸過或是新的東西或技能，會有意願接觸學習嘗試，並整合到原有自身的知識系統進行創新或是開創式的思考或嘗試 5.細節重視：魔鬼藏在細節裡，注重細節才有提升品質的潛力 [工具技能] - 必要要求 1.熟悉程度的文件處理製作能力(Google Docs, Google Sheets/Excel)、 2.中等的英文閱讀能力和基本的書寫能力 [工具技能] - 「大大」加分選項 1.對生成式AI工具(文字、圖片、影片、聲音、音樂等)的使用經驗或熟悉度，如：ChatCPT, Notion AI, Stable Diffusion, Midjourney等。 2.對語言的「讀寫」熟悉程度能力：泰文、韓文、日文、菲文(Tagalog)、葡文、印地語等 [其他說明] 1.本職務設定上可接受無相關經驗者或新鮮人，以便公司以內部設定的模式訓練，長期朝中高階職務的逐步培訓，因此興趣、態度、熱情、責任感等，會是本工作優先的考量依據(本職務需經過兩階段面試，從提供的履歷內容介紹，到面談過程均持續進行上述的觀察，並期待求職可以清晰明確的表達如何符合相關條件)。 2.入職後會有階段性的試用期，通過後將朝SEO優化師專案經理的規劃設定進行培養。 3.入職通過試用期後，並進一步通過公司內部基本職能的評測，將會開始安排負責專案，以成效進行最終評估導向，並設定專案績效獎金，給予同仁更多能激勵自己創造提升卓越的成效的動機和成就感。