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Tier-1 employer plus metro location and mid-level experience yield medium competition.
Requires GPU, driver, and hardware-architecture expertise, making cross-industry transfers difficult.
Explicit 4+ years plus low-level systems and GPU-specific skills indicate high shortlisting strictness.
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Develop and enhance GPU profiling libraries to support performance analysis for NVIDIA hardware.
Collaborate with multi-disciplinary and hardware architecture teams to design and verify GPU performance metrics.
Support profiling methodologies and tools across diverse platforms, from supercomputers to embedded systems.
B.Tech in EE/CS or equivalent with 4+ years experience, or M.Tech with 2+ years, or Ph.D.
Strong programming skills in C, C++, and Python with proficiency in data structures and algorithms.
Solid understanding of computer architecture (x86, ARM, GPUs) and operating system concepts.
Knowledge of software design principles for scalable software development.
Experienced in device drivers or system software development related to GPUs.
Familiarity with GPU APIs such as CUDA, OpenCL, OpenGL, Direct3D, or Vulkan.
Background in GPU application performance analysis and ability to read/write assembly for multi-processor architectures.