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【Hour Loop 飛輪電商】在2013年成立，並於2022年初在美國那斯達克上市。作為亞馬遜 (Amazon) 第三方賣家。在百萬競爭對手中，我們透過獨特的營運模式，成功實現十年來的持續成長，並脫穎而出，在2022年底躍升為亞馬遜 (Amazon) 前十名的賣家！歡迎對外商新創文化、電商產業有熱誠的人才加入我們的團隊！ 工作職責 開發設計內部系統，使其符合公司的需求和員工特性與業務部門/營運部門團隊進行必要之溝通協調工作。確立需求並明確規格，且持續推進與掌握相關業務之進展，與團隊共同合作完成目標。利用雲服務等技術開發出高擴展性、可靠性的解決方案追蹤系統運行狀況並及時處理問題熟悉並遵守內部開發準則與測試要求系統日常優化與維運作業 條件要求 熟悉任何一種物件導向程式語言熟悉雲端運算服務，如AWS或Google Cloud等良好的溝通能力和團隊合作精神。樂於學習新技術和工具 採用的技術包括但不限於： 前端：HTML, Java Script後端：Ruby on Rails, Python資料庫：MySQL持續整合與部署：Docker雲端運算服務：AWS, GCP 我們的優勢： 完善的新人培訓，幫助新人迅速了解產業知識與實作應用每週定期與Mentor 1 on 1 ，隨時掌握自己的學習狀況外商新創的工作氛圍讓你對專案有高度自主性與發揮空間升級並擴充既有的系統，清楚看到自己對全公司的影響力嚴謹的code review，打下穩固基礎獲得寫出clean code的能力可以自己選擇與公司系統相關的學習方向，主管支持你提升自我彈性工時與工作地點

This position focuses on the development of backend components of algorithmic high-frequency trading systems.You will be co-working with quantitative trading strategy developers to bring trading strategies online.The main programming languages are Rust and Python.【About Us】 Quantrend Technology focuses on building financial trading strategies across a variety of asset classes and global markets. We empower the paradigm shift from traditional quant to AI quant by using modern end-to-end deep learning models. The difference between traditional approaches and our proprietary solution is that our models can automatically extract robust and high-quality trading signals (Alphas), but traditional hand-crafted approaches often fail to do so. We are a performance-driven company, seeking agile and talented people to join our team. Our working environment is relaxed yet intellectually intense. If you are a tech-savvy individual who enjoys the challenges of solving difficult technical problems in a fast-paced, energetic environment, then this is the role for you. We value the contributions of trading strategy developers and offer lucrative dividends and annual bonuses to high-performance employees.【Responsibilities】 1. Lead and develop high-frequency trading system infrastructure for alpha research and live trading. 2. Optimize the performance of latency-critical high-frequency trading systems. 3. Implement high-frequency trading risk management / alert systems. 4. Implement the storage system for low-latency market data. 5. Implement high-frequency financial data preprocessing pipelines. 6. Implement performance analytics—including signal performance and post-trade analytics (e.g. slippage, fill-rate, and market impact reports) 7. Build up CI / CD with Docker containers and Kubernetes on AWS. 8. Write unit tests and integration tests.【Requirements】 1. Bachelor’s degree in computer science or equivalent experience. 2. Solid backend system implementation experience. 3. Expert-level knowledge of algorithms, design patterns, OOP, threading, multiprocessing, etc. 4. Knowledge of design and implementation of high-availability, high-throughput, and low-latency backend components. 5. 3+ years of experience with Rust / Python, or other programming languages, like C/C++, C#, Java, and Node. JS. 6. Familiar with SQL databases and NoSQL databases (like MongoDB). 7. Familiar with REST API and WebSocket. 8. Familiar with microservices, Docker containers, Kubernetes, and CI/CD. 9. Familiar with Git, software engineering, and agile software development. 10. Strong writing and verbal communication skills, ability to express complex concepts in simple terms. 11. Excellent analytical and problem-solving skills and extremely detail-oriented. 12. Strong project management skills, i.e. the ability to manage multiple tasks and deadlines in a fast-paced environment. 13. Self-motivated and fast-paced learner. 14. Commitment to the highest ethical standards and who act with professionalism and integrity at all times【Nice to Have】 1. Masters or Ph.D. in mathematics, statistics, physics, or other quantitative disciplines. 2. Experience in quantitative trading. Market-making experience is a plus. 3. Experience and in-depth knowledge of financial markets. 4. Experience in algorithmic trading and machine learning algorithms. 5. Experience developing distributed backtesting, simulation, and real-time systems. 6. Experience developing a tick simulator. 7. Experience working with streaming and historical time series data, including a variety of messaging systems and databases. 8. Experience with automated reporting, monitoring, and visualization. 9. Reasonable quantitative and statistical skills.