Quantitative Developer (Python)
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The Role:
This role sits within the Quant Research Technology team and focuses on building and scaling the core platform that supports global trading research and production systems. You will work on highly complex, distributed systems that power data science workflows, trading infrastructure, and large-scale compute environments. This is a hands-on engineering role with a strong emphasis on automation, reliability, and system performance.
Key Responsibilities:
- Design and architect core platform infrastructure for deploying and managing trading systems
- Build scalable, automated solutions with a focus on reliability and observability
- Support evolving trading workflows and research environments across global teams
- Develop and enhance a Python-based data science platform used by researchers
- Optimize and maintain mission-critical production systems and monitoring tools
- Scale infrastructure to support large compute environments (CPU/GPU clusters) and high-performance storage systems
- Automate complex operational processes to reduce overhead and improve efficiency
- Identify and implement improvements to system robustness and performance under high-stress market conditions
- Collaborate closely with researchers and engineers in a fast-paced environment
Required Qualifications:
- 4+ years of experience building and maintaining distributed systems at scale
- Strong focus on system reliability, availability, and performance
- Expertise in Python, including data science libraries (NumPy, Pandas/Polars, Cython)
- Experience with infrastructure and software automation
- Hands-on experience with observability and monitoring systems
- Strong problem-solving and troubleshooting skills
- Ability to work independently and adapt quickly in a dynamic environment
Preferred Qualifications:
- Experience with containerization tools (Docker, Podman, Kubernetes)
- Familiarity with infrastructure orchestration tools (Terraform, Ansible, Airflow)
- Exposure to large-scale data systems or high-performance computing environments
- Interest in low-latency or high-performance systems