Quantitative Developer - Software Optimisation and HPC Application Engineering

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 our 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.

You will join QRT as a Software Optimization and HPC Application Engineer, supporting education and enablement across Research and Trading engineering teams. This role focusses on rolling out and educating researchers and developers on best practices in high-performance computing, efficient CPU and GPU utilization, and leading proof of concepts and pilot projects involving novel system architectures. You will also contribute to QRT’s internal training codebases and assess emerging HPC/Cloud technologies for research workloads.

 

Your future role within QRT:

· Educate developers on CPU/GPU architecture and performance optimization.

· Support pilot projects and code migrations across CPU, GPU and other novel architectures ensuring optimal performance.

· Evaluate emerging HPC and Cloud-native technologies for research and trading workloads

· Collaborate with academic and industrial partners in the areas of software optimization and computational technology.

· Contribute to internal training resources and assist in technical interview processes

 

Your present skillset:

· Strong development skills in C++, Python, and CUDA

· Deep knowledge of Linux systems, NUMA, and parallel processing principles

· Familiarity with HPC and cloud storage systems (e.g. NVMe, Vast)

· Experience with profiling tools (e.g. Vtune, gprof, Valgrind, Nsight, RGP)

· Familiarity with distributed computing frameworks (e.g. MPI, Ray) and orchestration tools (e.g. Slurm, Kubernetes)

· Knowledge of hardware subsystems including CPUs, GPUs, NICs, and schedulers

· Strong communicator with an interest in technical education and system performance

 

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.