Join a leading global quantitative trading firm where technology drives every decision. For over 25 years, they've built world-class systems that push the limits of low-latency trading, high-performance computing, and large-scale data infrastructure. Their engineers work on mission-critical platforms that power research and trading in the world’s most competitive markets.
Responsibilities :
- Architect and evolve core research / trading infrastructure with a focus on automation, scalability, and resilience.
- Enhance the global Python data science platform supporting research at scale.
- Build and optimize distributed compute clusters (CPU / GPU) and multi-petabyte storage systems.
- Automate complex processes to reduce operational overhead.
- Improve reliability and performance to withstand extreme market conditions.
- Deliver rapid solutions in a high-impact, fast-paced environment.
Qualifications :
4+ years building and scaling distributed systems with high availability.Strong background in automation and infrastructure engineering.Proficiency in Python (Numpy, Pandas / Polars, Cython).Experience with observability and monitoring solutions.Familiarity with containerization (Docker, Kubernetes, Podman).Knowledge of orchestration tools (Ansible, Terraform, Airflow).Strong problem-solving, troubleshooting, and independent learning skills.