HPC R&D Engineer - Cloud Infrastructure

About the Role :

• We are seeking an exceptional and highly motivated HPC System R&D Engineer to join our team.
• In this role, you will be instrumental in developing and demonstrating next-generation HPC technologies, specifically focusing on their deployment and scalability across both on-premise and cloud infrastructures.
• You will identify limitations in current CPU and GPU-based solutions for large-scale AI deployments and architect innovative distributed frameworks and system-level solutions to overcome these challenges.
• Your work will directly impact the development of KLA's future tools, enabling breakthroughs in process control.
• Critically analyze existing HPC solutions based on CPU and GPU clusters to pinpoint bottlenecks and limitations in deploying AI-based solutions at scale on both on-premise and cloud infrastructures.
• Design, develop, and implement distributed frameworks and system-level solutions that enable seamless scaling of image processing and AI workloads from single GPUs to multi-node clusters with numerous GPUs.
• Focus on the challenges and opportunities of deploying HPC workloads in cloud environments, including resource management, scalability, and cost optimization.
• Install, benchmark, and rigorously evaluate pre-release hardware (CPUs, GPUs, interconnects, etc.) to assess their suitability for next-generation KLA tools.
• This includes identifying or developing relevant workloads for early-stage evaluation and prototyping.
• Conduct in-depth performance analysis of hardware and software stacks, identifying areas for optimization and improvement.
• Build functional prototypes and demonstrations of developed technologies on on-premise testbed clusters, paving the way for their integration into future KLA tools.
• Masters or PhD in Computer Science, Electrical Engineering, or a closely related field.
• Exceptional Bachelor's degree holders with significant relevant experience and an extraordinary track record will also be considered.
• Deep understanding of operating systems (Linux internals preferred), computer networks (high-speed interconnects like InfiniBand), and high-performance computing applications.
• Strong mental model of the architecture of modern distributed systems, including a comprehensive understanding of CPUs, GPUs, and various hardware accelerators.
• Proven experience with the deployment and scaling of deep-learning frameworks such as TensorFlow and PyTorch on large-scale on-premise or cloud infrastructures.
• Strong background in modern and advanced C++ concepts (including parallel programming paradigms).
• Excellent scripting skills in Bash, Python, or similar languages for automation, system administration, and data analysis.
• Good verbal and written communication skills to effectively collaborate with a diverse team and present technical findings.
• Things to Make us go Wow!
• Experience with the development and training of deep learning models using frameworks such as TensorFlow and PyTorch.
• Experience with building or significantly contributing to open-source operating systems and the software stack on pre-release hardware.
• Solid understanding of container infrastructure such as Docker or Singularity, and container orchestration platforms like Kubernetes for managing HPC workloads in the cloud.
• Active participation in C++ standards bodies or similar technical communities.
• Deep understanding and practical experience with HPC services offered by major cloud providers (AWS, Azure, GCP).
• Demonstrated expertise in performance profiling, tuning, and optimization of HPC applications.
• In-depth knowledge of high-speed interconnect technologies like InfiniBand and their impact on distributed application performance.

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(ref : hirist.tech)