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AXQ Capital

Quantitative Developer

  • Seen live on AXQ Capital's site yesterday
  • Mid level
Pay
Not stated
Location
Beijing
Open for
17+ days
First seen
Oct 18, 2026

Posting record

No flags

Open 17+ days

The posting's record, oldest first
  1. AXQ Capital's site dates the posting
  2. Ghostless first sees this listing
  3. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking AXQ Capital, so its true age is longer.

Last checked Nov 3, 2026.

How well do you match?

See how much of this posting your resume shows, and what it's missing.

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What the posting discloses

Not stated: Pay, real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Some employers add pay only on their own site. Check the original posting before you rule it out.

Skills mentioned

About the role

关于我们

AXQ 安贤投资 是一家全球量化投资机构。我们立足不同地域、资产类别和交易周期,持续构建多元化的投资优势。我们的策略植根于严谨的量化研究与深入的市场理解,并通过对数据、技术和人工智能的长期投入不断强化。我们汇聚来自全球顶尖高校及领先量化机构的优秀人才,倡导以好奇心、严谨精神和主人翁意识为基础的合作文化。在这里,最好的想法能够脱颖而出,每个人也能与公司共同成长。

岗位职责

作为 量化开发工程师(Quantitative Developer) ,您将与研究、开发与交易团队紧密合作,参与策略研究、系统化交易和风险管理领域的解决方案建设。您的工作包括:

  • 参与全球多市场接入及跨地域、多资产类别的数据、投研、回测和交易系统的开发与维护
  • 参与大规模金融数据管道与数据平台的建设,覆盖多市场、多资产数据的接入、清洗、存储与质量监控
  • 参与事件驱动的高频回测与模拟交易框架的开发,保障研究、回测与生产环境在数据语义与时间模型上的一致性
  • 参与订单管理、执行算法、组合构建与实时风控系统的开发与迭代,兼顾系统效率、正确性与稳定性

岗位要求

  • 国内外知名院校计算机科学、自然科学、工程或金融数学等相关专业本科及以上学历
  • 扎实的编程能力与计算机基础,熟练使用 Python(其他语言为加分项)
  • 扎实的数学与概率统计基础
  • 熟悉 Linux 系统使用,对网络、并发、数据结构与算法有扎实理解
  • 具有良好的工程习惯和出色的沟通能力
  • 具有解决新问题的勇气、热情和能力
  • 具有强烈的责任感
  • 欢迎应届毕业生及处于职业早期的候选人申请,相关行业经验为加分项

加分项:

  • 实习、开源项目或个人项目中有量化研究、金融数据处理或大规模数据/系统相关经验
  • 熟悉至少一门静态编程语言(C++ / Rust / Go)
  • 具有机器学习、数据分析或时序数据建模经验
  • 熟悉常见分布式系统/数据平台组件(Kafka、ClickHouse、Kubernetes 等)
  • 有 AI/LLM 工程实践(Agent、RAG、推理部署与优化等)
  • 有数学、物理、信息学或计算机等学科竞赛(如 ACM/ICPC、NOI、IMO、IPhO 等)获奖经历
  • 熟练使用 AI 辅助编程工具(如 Claude Code、Cursor、Codex 等)

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