High Performance Compute

The Research and Development (R&D) team at Hudson River Trading (HRT) builds and maintains the computers, networks, data storage, operating systems, and software that allow our trading strategies and research environment to operate worldwide 24/7. The Storage team within R&D manages hundreds of petabytes of storage to facilitate industry-leading AI/ML-based trading.

We are seeking an experienced Storage Engineer who enjoys being challenged, appreciates an open and collaborative organizational structure, and thrives in a fast-paced environment. In this role, you will manage our existing storage infrastructure and be responsible for the design, automation, and management of future storage solutions to support our large-scale research environment. This is an exciting opportunity to join a small team focused on HPC storage and help set the direction for storage solutions at HRT. You’ll have freedom to research, propose, and test new hardware and software to improve the performance and usability of our research environment.

Responsibilities

• Design, deploy and manage a variety of storage solutions
• Troubleshoot complex storage, OS, and networking issues
• Build tools to improve the performance and monitoring of storage clusters
• Research and experiment with new storage solutions

Qualifications

• Knowledge of distributed file systems used for large-scale cluster computing (Lustre, CephFS, GPFS, etc.) 
• Ability to design a home grown NAS storage solution with redundancy and high availability
• 3+ years of experience in HPC-like environments with large scale storage deployments greater than 1PB
• 3+ years of experience with scale-out enterprise storage solutions such as Isilon, VAST, NetApp, and Pure
• Extensive experience with Linux troubleshooting and NFS
• Strong knowledge of Linux, ZFS, and other Linux filesystems
• Proficient in Python and shell scripting 
• Strong cross-functional communication skills
• Ability to analyze and solve problems quickly in a fast-paced environment
• Exceptional time management skills and the ability to balance independent and collaborative workflows 
• Eager to learn and apply new skills

The estimated base salary range for this position is 150,000 to 250,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.