Machine Learning Engineer 機器學習工程師

17LIVE 招募機器學習工程師（MLE），配合快速的業務擴展，致力於透過 AI 技術優化產品內容與用戶體驗。您將負責全週期的機器學習服務開發與維運，確保系統在高流量環境下的穩定性。

主要職責

• 基礎架構設計：設計與實作具備高容錯、可擴展的雲端機器學習基礎設施。
• 跨團隊協作：與研發團隊（含資料科學家、PM 等）合作，運用 ML 解決商業挑戰。
• 效能優化：分析並增進子系統的效能、延展性與穩定性，支撐海量線上流量。
• 持續交付：定期上線 ML 新功能，持續優化用戶產品體驗。

基本條件

• 3 年以上機器學習開發經驗。
• 具備將 ML 服務部署至中大型流量系統的實務經驗。
• 卓越的邏輯分析與程式撰寫能力。
• 具備開放性思維、創造力及優異的跨團隊溝通能力。

加分條件

• 熟悉機器學習開發流程與維運（MLOps）。
• 精通任一語言：Python, C++, Scala, Go。
• 具備分散式計算（Spark/Hadoop）或深度學習框架（TensorFlow/PyTorch）經驗。
• 具備 AWS/GCP 部署經驗或 SQL/NoSQL 資料庫查詢優化經驗。
• 1 年以上後端程式開發經驗。
• Agentic AI 相關經驗(Prompt Engineering / Agentic Frameworks)。
• 英語溝通流利。

Join 17LIVE as a Machine Learning Engineer to drive product innovation and enhance user experience through AI. You will be responsible for designing, deploying, and maintaining high-performance ML services in a fast-paced environment.

Key Responsibilities

• Infrastructure Design: Build large-scale, fault-tolerant cloud infrastructure for ML services.
• Global Collaboration: Partner with cross-functional teams (Data Scientists, PMs, etc.) to solve business problems using ML.
• System Optimization: Enhance the efficiency, scalability, and stability of systems handling high concurrent traffic.
• Feature Deployment: Continuously deploy and iterate on ML features to improve user engagement.

Requirements

• 3+ years of experience in ML development.
• Proven track record of deploying ML services to high-traffic production environments.
• Strong analytical skills and proficiency in coding.
• Creative problem-solver with excellent cross-functional communication.

Preferred Qualifications

• Familiarity with ML development lifecycles and operations (MLOps).
• Proficiency in one or more: Python, C++, Scala, or Go.
• Experience with distributed computing (Spark/Hadoop) or Deep Learning (TensorFlow/PyTorch).
• Hands-on experience with AWS/GCP and SQL/NoSQL performance tuning.
• 1+ year of backend development experience.
• Familiarity with Agentic AI (Prompt Engineering / Agentic Frameworks)。
• Fluent in English.