关于我们

安贤投资（AXQ Capital）致力于以严谨的量化研究与先进的信息技术驱动投资。我们打造科学高效的量化研究框架，构建多市场多策略投资体系。策略布局覆盖全球股票统计套利、A股指数增强、CTA、股票日内、期货高频等领域，在全球市场部署运行，覆盖多个地区、资产类别及交易周期。自2018年成立以来，安贤持续为海内外投资者创造长期稳健的投资回报，资产管理规模稳步增长。公司在北京、上海、香港、纽约设有办公室，为国内员工提供海外交流与培训机会。

项目概览

安贤投资2026暑期实习项目面向全球顶尖人才。作为量化开发实习生（Quantitative Developer Intern），您将师从一位经验丰富的技术专家，在其指导下参与一项完整的量化系统开发与优化项目。公司提供业界一流的技术架构、充足的计算资源以及全程指导支持。您的工作内容可能涉及低延迟交易系统、实时数据处理、机器学习模型训练与预测、研究平台开发、风控系统构建或云计算架构优化等核心技术环节。项目具有明确的考核标准，您将在实习结束时向用人经理和公司合伙人展示工作成果。

实习安排

• 实习地点：北京
• 实习时长：6 月 29 日 – 9 月 4 日（共 10 周）
• 实习薪酬：2000 元 / 天 + 餐补
• 住宿安排：为异地实习生按需统一安排住宿

培训计划

• 6 月 29 – 30 日于北京开展集中培训与团建（QR Intern + QD Intern）
• 实习期间公司提供为实习生定制的系列讲座，系统补充量化知识
• 配备专属导师一对一带教，持续跟进项目进展与提供阶段性反馈

Return Offer

• Final Presentation 评定达到 A 或 S 级，即可获得全职 Return Offer
• 评定达到 S 级，Return Offer 将保证百万年薪，并安排前往纽约办公室参加培训
• 全职入职地点可在北京 / 上海之间，根据个人意愿及团队实际需求综合协商确定
  
  

岗位要求

• 国内外知名院校计算机、自然科学、工程学或金融数学本科及以上学历
• 扎实的代码能力，熟悉 Python，了解 Go 或 C++
• 熟悉 NumPy、Pandas 等数据处理工具
• 有 Linux 操作系统以及 Shell 编程经验
• 对计算机网络、数据结构和算法有深入了解
• 有优秀的沟通协调能力，思维缜密，注重细节

加分项：

• 有量化投资领域或互联网公司的实习经历
• 获得过国际或国内数学、物理、计算机等奥林匹克竞赛奖项

如遇任何问题，请联系我们：recruiting@axqcap.com

About Us

AXQ Capital is a global quantitative investment firm with offices in New York, Beijing, Shanghai, and Hong Kong. We pursue consistent alpha through rigorous scientific research and sustained investment in technology and data infrastructure. Our strategies are deployed across global markets, spanning multiple geographies, asset classes, and trading horizons.

Job Duties 

As a Machine Learning Researcher, you will develop ML/DL models to generate alpha from large-scale financial and alternative datasets. Working closely with portfolio managers and senior quantitative researchers, you will conduct research across a range of trading strategies within a fast, iterative research-feedback loop.

Qualifications

Below is a list of skills and experiences we believe are relevant. Even if you don’t consider yourself a perfect match, we still encourage you to apply because we are committed to helping our people grow and develop.

• Master’s or PhD from a top-tier university in a quantitative discipline (e.g., mathematics, physics, statistics, computer science, or related fields)
• Strong foundation in machine learning, statistics, and optimization, with deep expertise in at least one area such as time series modeling, NLP, or LLMs
• Strong communication skills and ability to collaborate effectively in a research-driven environment
• Experience with the Python scientific and ML ecosystem (e.g., NumPy, Pandas/Polars, PyTorch, TensorFlow)
• Proven ability to build and improve models that perform under noisy, non-stationary, and high-dimensional data conditions
• Intellectually curious, highly analytical, and driven to discover alpha in complex systems
• Self-motivated and highly productive, with strong ownership and a bias toward action
• Publications at top-tier venues such as NeurIPS, ICML, KDD, or IJCAI
• Strong track record in competitive ML platforms (e.g., Kaggle) or academic competitions
• Prior experience in quantitative research, systematic trading, or alpha signal generation