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GPU Performance Attainment Engineer

India, Hyderabad · Job Posted March 19, 2026
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Job Description

As a senior member of the pre-silicon performance attainment team, you will be a technical contributor that drives end-to-end delivery of solutions, directly contributing to, and coordinating workload optimization across multiple teams for inference and training of machine learning models. You will collaborate closely with software and hardware teams to plan, develop and optimize use cases. This is an exciting opportunity to work at the cutting edge of GPU computing, influencing design and software strategies to power future datacenter AI and ML deployments.

Job Responsibility

  • Debug performance issues and analyze data from the full-chip Emulation Platform, RTL Simulator, and Architecture and Roofline Models
  • Analyze model projection results and identify algorithm issues to find novel solutions for improving the accuracy of projection for different families of products, and over multiple generations
  • Get performance projections for kernels using an analytical model
  • Identify technical problems, break them down, summarize multiple possible solutions, and help the team to make progress
  • Automate processes related to performance infrastructure and data collection tasks, to enhance productivity and refine processes for improved efficiency
  • Engage with the workloads team to acquire and align on required workloads, run the selected workload traces on the performance simulator, analyze the performance results and metrics to root cause any anomalies
  • Collaborate with simulator team to bridge gaps between the performance numbers and the performance targets
  • Influence design trade-offs and optimizations by working closely with compiler, driver, library, and hardware engineers to achieve the highest performance for selected workloads
  • Innovate new algorithmic improvements that exploit the strengths of the hardware architecture to deliver the best possible machine learning performance

Requirements

  • Several years of experience in GPU pre-silicon performance analysis and debug
  • Proficiency with performance modeling and simulation tools
  • Strong understanding of GPGPU programming APIs and Machine Learning workloads
  • Expertise in C/C++ /Scripting (Python, Perl, Shell etc.)
  • Experience with hardware description languages such as Verilog is a plus
  • Familiarity with the software stack is a plus, preferably related to GPUs—such as applications, drivers, compilers, and firmware
  • Bachelor's or higher degree in Computer Science, Electrical Engineering, or a closely related field

Nice to have

  • Experience with hardware description languages such as Verilog is a plus
  • Familiarity with the software stack is a plus, preferably related to GPUs—such as applications, drivers, compilers, and firmware
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