【TW】Sr. AI Platform Engineer
薪資範圍:NT$ 1,300,000 - 2,000,000 (年薪)
公司名稱: 漸強實驗室 Crescendo Lab Ltd.
Bachelor's or Master's degree in Computer Science or related field 4+ years of experience in software engineering, with a focus on backend development Strong proficiency in languages such as Python, or Go Experience with cloud platforms (e.g., AWS, GCP, Azure) Familiarity with containerization and orchestration (e.g., Docker, Kubernetes) Knowledge of RESTful APIs and microservices architecture Understanding of distributed systems and scalable architectures Familiarity with CI/CD practices and tools 漸強實驗室的主要產品是 SaaS 平台 Messaging Analytics & Automation Cloud (MAAC)，以及 Conversation Analytics and Automation Cloud (CAAC)，為目前業界領先的 MarTech 解決方案。這兩項產品服務的企業客戶，包含數百家不同產業的知名跨國企業。在漸強你所開發的功能會真正影響到人們，在生活中也常常發現自己開發的功能正在被店家所使用。身為漸強工程團隊的一員，你會參與完整的產品開發週期，不只是交付需求，更可以提供你的想法，來影響產品走向，幫助產品成長。團隊成員都樂於分享且對技術非常有熱誠，主動學習追求各種新技術，每週都有工程討論會議，討論與分享技術大小事。我們擁抱非同步溝通，致力減少不必要的會議並尊重工程師的心流時間。自由透明的文化，可以自己安排工作時間，不受限制的假日天數，最重要的是，漸強追求彈性以及高效的工作環境。目前我們的後台每月發送近 2 億則個人化的訊息 並且與 2千多萬名的使用者互動，每日處理數 TB級 的數據來做分析以及 AI 應用。身為一位後端工程師，在這裡你會學習到如何處理百萬的流量，持續優化、建置彈性可靠的後端系統，並且有機會帶領小隊打造產品功能。你也將一起型塑工程團隊的文化、優化工作流程以及跨團隊合作方式，這會非常有趣且充滿挑戰，期待你的加入！ 更多資訊，歡迎參考我們的技術部落格 We are seeking an experienced AI/ML Platform Engineer to design, build, and maintain the backend infrastructure supporting our AI/ML systems. The ideal candidate will have strong software engineering skills, with a focus on creating scalable and efficient platforms for deploying and running AI/ML models. Key Responsibilities Design and implement robust, scalable backend systems for AI/ML model deployment Develop APIs and services to integrate AI/ML models with other applications Optimize performance and efficiency of AI/ML model serving infrastructure Implement data pipelines for preprocessing and feeding data into AI/ML models Ensure high availability, fault tolerance, and security of AI/ML systems Collaborate with data scientists and ML engineers to productionize models Monitor and troubleshoot production AI/ML systems公司地址:
台灣 臺北市其他:
Experience with AI/ML frameworks (e.g., TensorFlow Serving, ONNX Runtime) Knowledge of data pipeline technologies (e.g., Kafka, Airflow) Familiarity with MLOps practices and tools Experience with database systems (SQL and NoSQL) Understanding of AI/ML concepts and workflows Knowledge of monitoring and observability tools for large-scale systems -2024-09-17