威旭資訊股份有限公司

【能力需求】
・電機、資工、生醫、數學、物理等理工相關科系。
・對交易策略研究有強大的熱情。
・熟悉Python（必要）、機器學習（必要）

【加分項】
・具備基礎的金融相關知識與交易規則。
・熟悉C++或任ㄧ程式語言。

ICI Holdings 威旭資訊是一間專注於高頻交易、造市及套利交易的公司，我們進行量化研究並追求更好的交易策略。擁有領先全台的軟體研發團隊，並具備華爾街等級的FPGA設計技術，據此打造低延遲全自動交易系統；同時，交易策略橫跨股票、期貨及衍生性商品，且每日全球交易市值達數百億台幣。

其中，計量研究人員是結合統計、資訊和財金的一份職務，在整個計量研究的期間將會同時使用及學習到不同領域的知識並將其結合，以上不同領域知識包含(但不僅限於)市場微結構、統計、機器學習(Machine Learning)。

為了使工作順利，需大量利用程式工具來完成任務，因此需俱備Python、R或C++等程式語言的基本使用能力。在累積一定的研究成果後，也有機會依個人意願發展高頻交易、量化交易員職涯，建立自動交易策略。

【工作內容】
・金融數據分析（方法挑選、資料蒐集與分析）。
・計量模型研發（建立模型原型、回測）。
・AI演算法交易策略研究。

Required Skills
• Master’s degree in CS, EE, CE or a related technical field.
• Proficient in Modern C++.
• Expertise in C++ multithreading optimization.
• Familiar with Network Programming and network operation principles (experience with kernel-bypass networking is highly desirable).
• Knowledgeable in computer architecture with a focus on efficient utilization of hardware resources (experience with instruction-level optimizations such as SIMD is a plus).
• Experienced in Linux system programming.

As a C++ Software Engineer in our trading group, you will play a crucial role in implementing trading strategies in the market. Ideal candidates should excel in C++ multithreading optimization, be adept at efficiently utilizing CPU and memory resources to achieve better latency, and have a strong understanding of Network Programming and network principles (experience with DPDK or other network card accelerations is a plus). The role requires implementing trading algorithms with minimal latency. If you are passionate about programming optimization, eager to learn cutting-edge techniques, and find great satisfaction in reducing program and trading system latency, this position is a perfect fit for you.

Candidate Requirements:
• BS/MS degree above from EE, CE with 2+ years of relevant work experience
• Experience in high-speed interface design or knowledge in PCIE/ Ethernet/MIPI/DDR design or implementation is a plus
• Experience using System Verilog and at least two prior RTL design is a required.
• Demonstrated ability to tackle complex design challenges and implement effective solutions

Other Requirements:
• High self-motivated individual with good communication skill.
• English level – working level proficiency is a plus.

VICI Holdings' Hardware team is seeking a skilled FPGA Engineer to join our dynamic group. In this role, you will be pivotal in advancing our trading systems, contributing to the development and enhancement of cutting-edge technologies.

We boast the leading software development team in Taiwan and possess FPGA design technology in parallel with wall street trading firms. This expertise enables us to build low-latency, fully automated trading systems. Our trading strategies cover stocks, futures, and derivatives, achieving a daily global trading volume in the hundreds of millions dollars.

Roles/ Responsibilities:
• High speed IP interface design (such as PCIE gen 3, 4 / Ethernet, DDR etc.)
• In charge of FPGA design/ implementation/simulation.
• Transmission protocol layer development.
• Optimizing hardware for latency.
• Proficiency with Xilinx design environment.

【能力要求】
・具備大數據量化分析能力。
・熟悉選擇權定價理論，修習過財務工程相關學程。

【加分項】
・熟悉機器學習分析。
・具有開發交易系統經驗。
・對於開拓新市場有強烈企圖心。
・熟悉選擇權造市實務，具3年以下相關經驗者佳。

VICI Holdings 威旭資訊是一間專注於高頻交易、造市及套利交易的公司，我們進行量化研究並追求更好的交易策略。擁有領先全台的軟體研發團隊，並具備華爾街等級的FPGA設計技術，據此打造低延遲全自動交易系統；同時，交易策略橫跨股票、期貨及衍生性商品，且每日全球交易市值達數百億台幣。

我們目前正在積極拓展亞洲選擇權市場業務，持續招募 選擇權交易員(高頻/量化交易員) 加入我們。

【工作職責】
・開發選擇權量化交易策略。
・評估其他亞洲市場選擇權交易可行性。
・提升目前選擇權造市業務市佔率與獲利。

Required Skills:
• Proficiency in Python with data libraries such as Pandas and NumPy.
• Hands-on experience with one deep-learning framework (PyTorch or TensorFlow).
• Comfortable with Git / GitHub workflow and AI pair-programming with LLMs.
• Strong prompt-engineering skills to steer LLMs for code and insights.
Preferred Qualifications:
• Final-year undergraduates or second-year master's students in EE, CS, Statistics, Mathematics, Physics, Financial Engineering, or related fields.

Other Requirement:
• Highly curious, self-motivated, with strong analytical thinking.
• Effective communicator in English and Chinese.

• The AI Data Scientist/Internship/Campus hire develops talent skilled in AI pair-programming workflows and AI-agent architectures to accelerate data exploration, rapid prototyping, and strategy evaluation.

• Outstanding interns may convert to full-time roles and continue pioneering the intersection of quantitative trading and Generative AI.

Roles/ Responsibilities:
• Use LLM-powered AI pair-programming to explore, clean, and analyze large datasets.
• Apply AI-agent architectures to automatically generate and evaluate strategies.
• Develop AI-driven applications for automated news analysis, investment recommendations, and risk management decision-making.
• Build, fine-tune, and evaluate AI or LLM models to identify key features from data and produce analytical reports.
• Collaborate with researchers and engineers to integrate models or insights into internal systems and monitor performance.

Requirements
· M.S. or above in CS/EE/Data Science preferred; equivalent practical achievements considered.
· Proficient with AI coding tools (Cursor, Claude Code); adept in spec engineering and test-driven development (TDD). Deliver rapid 0→1 with AI and drive 1→100 iterative improvement.
· 2+ years in LLM with PyTorch or TensorFlow; hands-on experience training and fine-tuning models end to end.
· Fluency in the LLM ecosystem (LangGraph, Ollama, OpenAI SDK) to rapidly prototype and ship services.
· Strong experiment design, problem decomposition, and cross-team communication with an emphasis on observability and operability.
· Effective communication in Mandarin and English; able to write technical docs and present externally.

R&R

· Co-design experiments with quants to translate model outputs into tradable signals, with offline/online backtesting and A/B testing.
· Design and build AI agents (RAG, tool use, task planning) to boost strategy research and trading execution efficiency.
· Apply prompt engineering, MoE, LoRA, quantization, and distillation to improve the perf–cost curve and inference latency.
· Specialize fine-tuning and alignment (SFT/DPO) for financial text—disclosures, news, social, earnings—to improve event and sentiment inference.
· Adopt MLOps best practices (containerization, CI/CD, feature/model versioning) to increase velocity and compliance.
· Track frontier research and lead internal tech sharing to inform model selection and architecture evolution.