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AXQ Capital

Head of Machine Learning Infrastructure

AXQ Capital · Beijing; Shanghai

Posted about 3 months ago

or apply directly on AXQ Capital's site. We never take the application ourselves.

Is this posting real?

This role has been open
80 days
AXQ Capital's roles stay open a median of 81 days
Reposted
No
Salary listed
No
34% of AXQ Capital's roles list one
Ghost-job risk at AXQ Capital
high
27 stale, 0 reposted of 29 open
Hiring momentum
32 roles opened in the last 90 days
↑ up vs. the prior 90 days
Last confirmed on the employer's board
2026-10-23

Measured from postings appearing on and disappearing from AXQ Capital's own greenhouse board since 2026-08-03. Full hiring picture for AXQ Capital.

About this role

The Head of Machine Learning Infrastructure will report to the CTO and oversee the core computing and platform infrastructure for machine learning and quantitative research. This includes managing GPU/CPU clusters, distributed training, and a machine learning platform to support large-scale feature engineering and model training with efficient data processing capabilities. The role involves building and optimizing systems for high performance, scalability, and cost-effectiveness while enhancing research and engineering efficiency.

Our read on this posting2.4out of 5
benefits
1/5
freshness
1/5
career value
5/5
role clarity
5/5
pay transparency
0/5

Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of AXQ Capital as an employer.

What you need

  • 8 years of experience in machine learning infrastructure, distributed systems, platform engineering, high-performance computing, or cloud infrastructure
  • Experience managing infrastructure or platform teams and complex system architecture
  • Strong foundation in Linux, networking, storage, distributed systems, and container technologies
  • Familiarity with GPU computing, distributed training, and large-scale machine learning workloads
  • Experience with task scheduling, data I/O, feature engineering, and system performance optimization
  • Proficiency in at least one programming language such as Python, Go, C++, Rust, or Java

Nice to have

  • Experience in quantitative investment, hedge funds, machine learning platforms, or large-scale research computing platforms
  • Experience building GPU clusters, distributed training, or HPC platforms
  • Familiarity with technologies such as PyTorch Distributed, Ray, Slurm, NCCL, CUDA, RDMA
  • Experience with large-scale feature engineering platforms, data pipeline systems, or PB-level data processing
  • Experience optimizing GPU resources and costs on cloud platforms like AWS, GCP, Alibaba Cloud, or Tencent Cloud

Worth weighing

  • No salary listed
  • Role involves significant responsibility in managing complex systems and infrastructure
  • Focus on large-scale data processing and machine learning, which may require staying updated with evolving technologies

Summarised from AXQ Capital's posting. Read the full original.

Listed by AXQ Capital on their greenhouse job board, last confirmed open on 2026-10-23. PitchMeAI is not the employer.

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