Expose limitations in existing solutions, based on clusters of CPUs & GPUs, to deploy AI-based solutions on on-prem & cloud infrastructures at scale.
Develop distributed frameworks and system-level solutions that enable scaling out image processing & AI loads from single GPU to multi-node clusters with multiple GPUs.
Install, benchmark, and evaluate pre-release hardware for early-stage evaluation and prototyping by identifying (or developing) relevant workloads.
Minimum Qualifications
Masters / PhD in Computer Science or related fields; bachelors degree holders with relevant experience and extraordinary track-record will also be considered.
Deep understanding of operating systems, computer networks, and high performance applications
Good mental model of the architecture of a modern distributed systems that is comprised of CPUs, GPUs, and acceler...
Ready to Apply?
Submit your application for R&D Engineer, HPC Systems at KLA