Sr. HPC Engineer - Platforms

PsiQuantum • Palo Alto, CA

9d

About The Position

PsiQuantum is hiring a Senior HPC Engineer to design, develop, and optimize high-performance computing software using NVIDIA GPUs, AMD CPUs, and MPI for distributed and parallel computing. The role requires a foundation in computational science and parallel algorithms, along with expertise in GPU and CPU optimization. The engineer will help design and implement scalable solutions for HPC clusters so that high-performance applications run efficiently as nodes scale to support expanding workloads.

The position involves developing parallel software, optimizing algorithms and cluster configurations, profiling and benchmarking applications across scaled environments, and working with scientists, engineers, and IT staff. The role also includes documenting code and scaling processes and reporting performance results to stakeholders.

Requirements

• Bachelor's or master's degree in computer science, electrical engineering, computational science, or a related field.
• At least 3 years of HPC development experience focused on parallel and distributed computing, including experience with scalable systems.
• At least 5 years of previous scientific software development experience.
• 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 cluster scaling and software optimization for distributed, multi-node environments.
• Strong proficiency in C/C++, Python, and Ansible, Terraform, or Packer.
• Ability to work independently and collaboratively, with strong problem-solving, communication, and attention-to-detail skills.

Nice To Haves

• Advanced degrees or relevant certifications.
• Familiarity with HPC environment management tools such as Slurm or PBS.
• Experience with Singularity or Docker in an HPC context.
• Understanding of cloud-based HPC scaling solutions or hybrid HPC environments.
• Experience with GPU-using machine learning frameworks such as TensorFlow, PyTorch, or PySCF.

Responsibilities

• Design and implement HPC software solutions using NVIDIA GPUs and AMD CPUs, maximizing computational efficiency and speed.
• Use MPI, CUDA, OpenMP, and other parallel computing techniques to help applications scale across multicore and multi-GPU systems.
• Contribute to the design, deployment, and scaling of HPC nodes and optimize software and cluster configurations.
• Identify and implement algorithms suited to GPU and CPU computing for complex and data-intensive workloads, maintaining performance as node counts increase.
• Profile and benchmark HPC applications across scaled environments to identify bottlenecks and maintain consistent performance across nodes.
• Work with scientists, engineers, and IT staff to optimize and scale HPC applications for research and production environments.
• Document code and scaling processes, and report performance metrics, improvements, and results to stakeholders.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior