HPC Software Engineer

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data driven group implementing a scientific approach to investing. Combining data, research, technology and trading expertise has shaped QRT’s collaborative mindset which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high quality returns for our investors.

We are seeking a HPC Software Engineer to work on the development of a scalable research platform that will serve as the foundation for research teams across the organization to access HPC infrastructure and compute. This will involve the development of tools to manage job submission, scheduling, launching, and observability across a range of environments with the goal of streamlining workflows, optimizing resource utilization, and lowering barriers to innovation. You’ll work at the intersection of software engineering, infrastructure, and research, driving the development of a platform that enables cutting-edge computation. 

Your future role within QRT 

• Design and develop scalable platforms to expose compute resource to researchers across a range of environments in a HPC context 

• Implement systems for resource scheduling and task management to support research workflows 

• Build libraries to enable researchers to submit and monitor workloads efficiently for both research and production pipelines 

• Build services to facilitate the automated management of large compute clusters and host lifecycle 

• Integrate and optimize distributed compute systems, particularly GPU-accelerated workloads 

• Collaborate with researchers and cross-functional teams to deliver tools that scale computational research 

Your Present Skill Set 

• 5+ years development experience writing high-quality, testable code using C++ or equivalent (C, Go, Rust), as well as experience with Python 

• Proven expertise in building robust distributed systems at scale 

• Flexible in adopting new technologies and a proactive approach to continuous skill development 

• (Preferred) Knowledge of scheduling systems (eg. Slurm) and workload management in large HPC environments 

• (Preferred) Experience optimizing GPU-accelerated workloads (CUDA, NCCL) 

• (Bonus) Experience working within or supporting quantitative research teams 

QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.