HPC Compute Architect
This organisation is a pioneer in high-performance computing for quantitative research and trading. They operate some of the largest and most sophisticated distributed compute clusters, with extensive GPU and CPU infrastructure, on-premises data centres, and a focus on optimising compute, network, storage, and power efficiencies. Their talented teams and state-of-the-art infrastructure are fundamental to their ongoing success and innovation in the competitive world of quantitative finance.
Your Future Role:
As a Senior Systems Engineer, you will be responsible for maintaining and improving the organisation's extensive HPC environment that supports live trading and research activities globally. Your role will involve designing and implementing scalable solutions, performing hardware upgrades, and automating critical infrastructure tasks. You will be integral to ensuring the system's resilience, performance, and adaptability in a fast-paced, high-stakes environment.
Key Responsibilities:
- Lead initiatives to optimise large-scale distributed compute clusters, focusing on scalability and robustness.
- Develop automation scripts and tools to streamline hardware provisioning, system updates, and routine maintenance.
- Troubleshoot complex hardware and software issues promptly, minimising downtime.
- Conduct performance analysis and tuning to maximise throughput and reduce latency.
- Collaborate with vendors and internal teams to implement new hardware and software solutions.
Your Current Skills & Strengths:
- Proven experience with deploying, configuring, and troubleshooting Linux/UNIX systems at scale.
- Advanced scripting skills in Python and Shell for automation and system management.
- Familiarity with configuration management frameworks and monitoring tools.
- Strong organisational skills with excellent attention to detail.
- Effective communicator with the ability to work collaboratively across multiple teams and stakeholders.
Additional Plus Points:
- Experience with Debian or Ubuntu environments.
- Knowledge of GPU hardware and optimisation techniques.
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