HPC Systems Engineer | Experienced Hire

About the role

As a member of our Platform Development team, you will be instrumental in building and optimizing high-performance trading systems, research compute clusters, databases, support systems, and more. You will heavily utilize Linux and Windows internals while working on servers in our HPC environment.

Responsibilities

• Automate and evolve our library of home-grown tools, written primarily in Python and Bash, to automate monitoring and maintenance, allowing you to focus on performance-related issues and projects.
• Collaborate with Strategy Developers, Quantitative Researchers, and trade-supporting application teams to translate complex problems into scalable solutions.
• Coordinate with IT infrastructure teams, including storage and networking, to identify and implement the best solutions.
• Optimize operating systems and batch workflows for performance.
• Dive deep on root-cause analysis of systems issues.
• Integrate solutions into our systems effectively and efficiently.
• Oversee all aspects of our HPC environment, including the scheduler, parallel filesystems, GPUs, and interconnects.
• Implement and optimize high-performance storage solutions, including Lustre, VAST, and GPFS, to efficiently support and enhance cluster performance.
• Develop strategies to ensure optimal resource allocation and scalability, using analytics to forecast needs and design efficient, reliable systems.
• Utilize monitoring and diagnostic tools to quickly pinpoint failures, streamline troubleshooting processes, and ensure the timely recovery of disrupted workflows.

Requirements

• A Bachelor’s degree in Engineering, Computer Science, Information Systems, or a related discipline.
• 5-7 years of progressive experience building Linux and/or Windows based HPC based platforms.
• Familiarity with kernel-level and I/O subsystem tweaks and tools such as sysctl, strace, tcpdump, and netstat.
• Recent hands-on experience with automation in Python or other tools.
• Experience administering Lustre, GPFS, VAST, or other parallel filesystems.
• Understanding of resource schedulers like HTCondor, SLURM, or similar.

About Susquehanna

Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.