Senior Quant Research Infrastructure Engineer

Millennium

Hong Kong

On-site

HKD 900,000 - 1,300,000

Full time

14 days+

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Job summary

Millennium in Hong Kong seeks a technically seasoned engineer to own the firm's core infrastructure for quantitative research and trading. You will design, build, and maintain data pipelines and compute environments, ensuring reliability, scalability, and integration of AI-native capabilities into the research stack.

You will collaborate with Quant Researchers and other teams to deploy robust tooling, observability, and automation.

Qualifications

  • 3-5 years of professional experience in quantitative development or strong AI/LLM engineering with ownership of complex infrastructure.
  • Proven end-to-end ownership of significant trading/research/AI infrastructure.
  • Deep expertise in modern C++ and Python in HPC contexts.
  • Experience with large-scale data infrastructure (real-time streaming and historical data).
  • Strong background in cloud computing (AWS, GCP, or Azure) and parallel computing.

Responsibilities

  • Design, build, and maintain core quant pipelines, data infra, and compute environments.
  • Ensure reliability, scalability, and performance of critical systems for research and trading.
  • Drive architecture for data/compute platform including AI-native capabilities integrated into the stack.
  • Collaborate with researchers and dev teams to meet requirements and integrate components.
  • Own deployment, monitoring, and health of production and research systems; improve observability and AI-assisted operations.

Skills

C++
Python
Cloud computing
Kubernetes
DevOps
LLM engineering
Agent frameworks
SQL/NoSQL

Tools

Docker
Kubernetes
Apache Spark
Redis
Dask
Terraform
CloudFormation
GitHub Actions
GitLab CI

Job description

Millennium in Hong Kong seeks a technically seasoned engineer to own the firm's core infrastructure for quantitative research and trading. You will design, build, and maintain data pipelines and compute environments, ensuring reliability, scalability, and integration of AI-native capabilities into the research stack.

You will collaborate with Quant Researchers and other teams to deploy robust tooling, observability, and automation.

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