Skip to content
CV Rocket
Get started
How it worksThe enginePricingBlogContactSign in

Open nowPosted 18 days ago

Machine Learning Infrastructure Engineer

AXQ Capital17 open roles

Where
Beijing
Get the CV for this job

From $25 per CV, paid once. No subscription.

Your applicationOpen nowMachine Learning Infrastructure EngineerAXQ Capital · Beijing

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on AXQ Capital's own form.

The reply lands in your private mailbox

3×more interviews than doing it yourself with ChatGPT.

The clock on this job

Early applications get read.

13.1% of postings close within 7 days. Measured by our own scanner across the market. AXQ Capital postings stay open a median of 26 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.1%7 days
  4. 21.1%14 days
  5. 35.8%30 days
  6. 59.0%60 days
This job: posted 18 days ago

AXQ Capital median: 26 days open

The posting

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。

岗位使命

作为机器学习基础设施工程师（Machine Learning Infrastructure Engineer）你将参与建设 AXQ 面向量化研究与机器学习的计算和平台基础设施，与 Infrastructure 团队及研究、工程团队紧密合作，提升特征计算、模型训练、实验迭代与推理任务的效率和可靠性。

我们面向 PB 级数据处理与大规模机器学习训练场景，持续优化 GPU/CPU 计算资源、分布式计算、存储与数据访问、机器学习平台及开发者工具。

你将参与相关基础设施系统与平台工具的设计、开发与交付，帮助研究人员更高效地使用计算资源，让研究工作流具备可扩展、可复现、易使用和成本高效的特性。

主要职责

  1. 计算集群与任务调度：建设和优化 GPU/CPU 资源管理与任务调度系统，提高计算资源利用率和任务运行效率。
  2. 分布式训练与计算：支持多 GPU、多节点计算任务，优化数据加载、任务并行、节点通信与故障恢复。
  3. 数据访问与性能优化：优化大规模数据读取、缓存与存储访问，定位并改善计算、网络及 I/O 瓶颈。
  4. 机器学习平台与研究工具：开发任务提交、实验管理、开发环境及依赖管理工具，提升研究效率与可复现性。
  5. 训练与推理基础设施：支持模型训练、批量及在线推理任务的部署运行，完善版本管理、监控与故障恢复。
  6. 自动化与稳定性建设：建设自动化运维、监控告警、权限管理与资源配额能力，提升系统可靠性。
  7. 需求落地与使用体验：与研究和工程团队协作，将共性需求转化为易用、可复用的平台能力。

岗位要求

  1. 具备基础设施、平台工程、分布式系统、高性能计算或机器学习相关技术基础，能够参与模块设计、开发、部署与问题排查。
  2. 扎实的 Linux、网络、存储和操作系统基础，能够分析资源使用情况，定位性能与稳定性问题。
  3. 熟练掌握 Python、Go、C++、Rust、Java 等至少一门编程语言，具备良好的编码习惯和工程意识。
  4. 了解容器、任务调度与资源管理，了解或熟悉 Kubernetes、Slurm、Ray 或同类系统中的至少一种。
  5. 理解机器学习模型训练和推理的基本流程，有实际模型训练或相关项目经验，了解数据 I/O、计算资源和运行环境的要求。
  6. 了解 CI/CD、Infrastructure as Code、监控告警及自动化运维，重视系统的可观测性、可复现性与故障恢复能力。
  7. 具备良好的学习、沟通与协作能力，能够理解研究需求，分析技术取舍并推动方案落地。

加分项

  • 有量化投资、对冲基金、机器学习平台或大规模研究计算平台经验。
  • 有大规模特征工程、数据管道、分布式存储或 PB 级数据处理经验。
  • 有模型服务、批量推理或在线推理基础设施建设经验。
  • 有公有云、混合云资源管理与 GPU 成本优化经验。
  • 有 GPU 集群建设、分布式训练性能调优经验，或熟悉 PyTorch Distributed、CUDA、RDMA 等相关技术。
  • 熟悉 Claude Code、Codex 等 AI coding tools，并有将其融入开发流程或建设配套工具的实践。
From $25, paid onceGet the CV for this job

What happens when you press

One press. We do the rest.

  1. A CV for this posting

    Written against AXQ Capital's own wording, from every piece of relevant proof in your profile.

  2. 25 readers review it

    Recruiter, hiring manager, skeptic and more read every draft, round after round. You get the best round.

    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on AXQ Capital's form

    Our application engine gets through the hardest forms there are. Where a question needs you, AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

    An application in CV Rocket: every answer filled in on the employer's form.

  4. Every reply, sorted

    AXQ Capital's answer lands in your private mailbox, and we classify it on arrival: interview, question, rejection.

    The CV Rocket inbox: each employer reply classified as an interview, an action or a rejection.

  5. Reply with AI

    AI helps you write the email, checks it and sends it. We show you whether the recruiter read it.

  6. The interview in your calendar

    Full integration with your calendar. The invitation goes straight in.

    An interview invitation in the CV Rocket inbox, added to the candidate's calendar.
Get the CV for this job

From $25 per CV, paid once. No subscription.

Why it works

3×

more interviews than doing it yourself with ChatGPT.

ChatGPT writes a CV and never learns what happened to it. We see every reply. For each CV we know:

  • How it was written, and how the review scored it
  • When we applied, and how long after the posting went up
  • Which posting, which company, which city
  • Who got the interview, and who heard nothing

That is how we know which CVs get called.

Get the CV for this job

From $25 per CV, paid once. No subscription.

The numbers game

More applications. More interviews.

Every application goes out with its own CV, written for that posting and paid once. Send enough of them and the law of large numbers finds you the job.

Get the CV for this job
By hand5–10
With CV Rocket100
applications a day

Nearby

Live postings like this one

Same employer first, then the same role elsewhere.

Before you press

Straight answers

Get the CV for this job

From $25 per CV, paid once. No subscription.

What if my background isn't good enough?

We make the most of the background you have. The CV uses every piece of relevant proof your profile holds, and one of the 25 readers reads your whole profile and flags what the CV left out.

Do you really apply for me?

Yes, on the employer's own form, the hardest ones included. Where a question needs you, you answer it right there and AI suggests the best answer. Don't want us applying from our IP addresses? Use our Chrome extension: we apply straight from your own browser.

Is it a subscription?

No. You pay once per CV, from $25. Every application goes out with its own CV, written for that posting.

One job. One CV.
Paid once.

Pick the posting you want. We write for it, apply for you and catch the reply.

Get the CV for this job

From $25 per CV, paid once. No subscription.