GPU HPC Software Engineer – AI Systems & Multi-GPU

California Polytechnic State University-San Luis Obispo; San Luis Obispo (CA); On-site; USD 111,000 - 127,000; Full time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Educational benefits

Job summary

Cal Poly ITS is seeking an experienced software engineer to empower faculty, researchers and students to leverage high-performance computing and AI infrastructure anchored by the NVIDIA DGX‑B200 system.

You will develop scalable software tools and workflows for large-scale ML/DL training, fine-tuning, and deployment, bridging GPU-oriented engineering with research-focused software support and consulting.

Qualifications

• Bachelor’s degree in a related field with four years of relevant experience.
• Advanced degree may substitute for experience.
• Proven experience with Python and performance-oriented languages (C++/CUDA) for AI/ML software.
• Experience with distributed computing and multi-GPU workloads, including CUDA toolkits and container runtimes.
• Experience with PyTorch, TensorFlow, or JAX and reproducible research workflows.
• Containerization and orchestration using Docker, Kubernetes, Slurm, and Ray.

Responsibilities

• Develop and scale software solutions, tools, and workflows for large-scale ML/DL training, fine-tuning, and deployment.
• Architect software pipelines and optimize workload performance across multi-GPU environments.
• Bridge GPU-oriented engineering with research-focused software support and consulting.

Skills

Python/C++/CUDA

Multi-GPU parallelism

AI/ML frameworks

Docker/Kubernetes/Ray

Linux systems

Education

Bachelor’s degree in related field

Advanced degree substitution for experience

Tools

Docker

Kubernetes

Slurm

Ray

CUDA toolkit

Job description

Cal Poly ITS is seeking an experienced software engineer to empower faculty, researchers and students to leverage high-performance computing and AI infrastructure anchored by the NVIDIA DGX‑B200 system.

You will develop scalable software tools and workflows for large-scale ML/DL training, fine-tuning, and deployment, bridging GPU-oriented engineering with research-focused software support and consulting.