Sr. HPC Engineer - Platforms

The role

You will design, develop, and optimize HPC software solutions using NVIDIA GPUs, AMD CPUs, and MPI. You will also design and implement scalable solutions for HPC clusters to ensure efficient performance as nodes scale.

What you will do

• Design and implement software solutions that harness NVIDIA GPUs and AMD CPUs.
• Employ MPI, CUDA, OpenMP, and other parallel computing techniques.
• Contribute to the design, deployment, and scaling of HPC nodes.
• Optimize software and cluster configurations for seamless scaling.
• Identify and implement algorithms suited for GPU/CPU computing.
• Conduct profiling and benchmarking of HPC applications using tools like NVIDIA Nsight, AMD μProf, and Intel VTune.
• Work with scientists, engineers, and IT staff to optimize applications.
• Create documentation for code and scaling processes.
• Report on performance metrics and results to stakeholders.

Required qualifications

• Bachelor's or master's degree in computer science, Electrical Engineering, Computational Science, or a related field.
• 3+ years of experience in HPC development, with a focus on parallel and distributed computing, and experience with scalable systems.
• 5+ years previous experience in scientific software development.
• Proficiency in CUDA and familiarity with NVIDIA’s HPC software stack, including cuDNN, NCCL, and TensorRT.
• Expertise in MPI, OpenMP, and other parallel programming paradigms.
• Strong understanding of scaling clusters and optimizing software for distributed, multi-node environments.
• Strong proficiency in C/C++, Python, and Ansible / Terraform / Packer.
• Familiarity with profiling and performance optimization tools (e.g., NVIDIA Nsight, AMD μProf, Intel VTune).
• Ability to work independently and as part of a team.
• Excellent problem-solving abilities.
• Strong communication skills.
• Keen attention to detail.

Nice to have

• Advanced degrees or relevant certifications.
• Experience with Slurm, PBS, or other job scheduling and resource management tools.
• Knowledge of Singularity or Docker in an HPC context.
• Understanding of cloud-based HPC scaling solutions or hybrid HPC environments.
• Experience with machine learning frameworks that utilize GPUs, such as TensorFlow, PyTorch, or PySCF.

About the company

PsiQuantum's mission is to build the first useful quantum computers using silicon photonics. The company is building utility-scale quantum computers in Brisbane, Australia, and Chicago.