Provide leadership and strategic mentorship on the management of large-scale HPC systems including the deployment of compute, networking, and storage
Develop and improve our ecosystem around GPU-accelerated computing including developing scalable automation solutions
Build and nurture customer and cross-team relationships to consistently support the clusters and address changing user needs
Support our researchers to run their workloads including performance analysis and optimizations
Conduct root cause analysis and suggest corrective action
Proactively find and fix issues before they occur
Build innovative tooling to accelerate researchers' velocity, troubleshooting, and software performance at scale

Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience
Minimum of 8+ years of experience crafting and operating large scale compute infrastructure
Experience with AI/HPC job schedulers and orchestrators, such as Slurm, K8s or LSF
Applied experience with AI/HPC workflows that use MPI and NCCL
Proficient in using Linux including Centos/RHEL and/or Ubuntu Linux distributions
A solid understanding of container technologies like Enroot, Docker and Podman
Proficiency in one scripting language (Python, Bash) and at least one compiled language (Golang, Rust, C, C++...)
Experience analyzing and tuning performance for a variety of AI/HPC workloads
Excellent problem-solving to analyze complex systems, identify bottlenecks, and implement scalable solutions
Excellent communication and teamwork skills, with the ability to work effectively with diverse teams and individuals
Passion for continual learning and staying ahead of new technologies and effective approaches in the HPC and AI/ML infrastructure fields.

Senior AI-HPC Cluster Engineer – MLOps

Key skills