HPC / Cuda Software Engineer

1 month ago

Chennai, India KLA Full time

Job Description

KLA’s AI Advanced Computing Labs is looking for an extraordinary HPC System R&D Engineer to join its team to develop system-level HPC technologies that would form the foundation of next-generation clusters used in KLA tools. The technologies would be developed and demonstrated on on-prem clusters that serve as testbeds for next-generation KLA tools.

Your Day-to-day Roles


  • Expose limitations in existing solutions, based on clusters of CPUs & GPUs, to deploy AI-based solutions on on-prem & cloud infrastructures at scale.
  • Develop 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.
  • Explore modern HPC systems software (such as new distributions of linux) for adoption into KLA’s tools.


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 accelerators.
  • Experience with deployments of deep-learning frameworks based on TensorFlow, and PyTorch on large-scale on-prem or cloud infrastructures.
  • Solid understanding of container infrastructure such as Docker or singularity, and Kubernetes.
  • Strong Scripting Skills in Bash, Python, or similar.
  • Good communication.


Things to Make us go Wow


  • Hands-on experience in architecting, building, and maintaining (against all odds) large scale distributed HPC clusters.
  • Experience with model development on DL frameworks such as TensorFlow, and PyTorch
  • Experience with building open-source operating systems and software stack on pre-release hardware.
  • Hands-on involvement with cluster management tools (such as Prometheus, Grafana), scheduling and resource management (like SLURM, PBS, MPI/OSHMEM), and virtualization technologies (such as KVM/VMWare/Nutanix)
  • Experience in working with developers who use clusters & sys-admins who maintain clusters

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