GPU Software Engineer

Requirements

• Master's Level Degree and 2+ years related work experience; Bachelor's Level Degree and related work experience of 4+ years **Minimum qualifications** - BS/MS in CS, EE, or related field. - 3–6 years of professional experience, including 2+ years focused on CUDA-based image processing. - Strong C++17/20 fundamentals; solid understanding of parallel algorithms and data layouts (pitch-linear, planar, interleaved). - Practical experience with Nsight profiling, occupancy analysis, and kernel optimization (tiling, warp-level intrinsics, streams). - Experience with OpenCV (including CUDA paths), and at least one of: NPP, cuFFT, cuBLAS. - Comfortable on Linux; CMake, Git, code reviews, and automated testing. **Preferred qualifications** - DMA/zero-copy, pinned memory. - Texture memory and surface writes for image sampling; CUDA Graphs and stream concurrency. - Familiarity with image feature extraction and classification - Exposure to ML inference acceleration (TensorRT/cuDNN) for CV tasks is a plus, but core focus is classical image processing. - Experience with performance modeling (roofline), and multi-GPU awareness (NCCL) is a bonus. - Experience with sharding, Tensor parallelism, etc Base Pay Range: $114,800.00 - $195,200.00 Annually Primary Location: USA-CA-Milpitas-KLA KLA’s total rewards package for employees may also include participation in performance incentive programs and eligibility for additional benefits including but not limited to: medical, dental, vision, life, and other voluntary benefits, 401(K) including company matching, employee stock purchase program (ESPP), student debt assistance, tuition reimbursement program, development and career growth opportunities and programs, financial planning benefits, wellness benefits including an employee assistance program (EAP), paid time off and paid company holidays, and family care and bonding leave.
• Interns are eligible for some of the benefits listed.
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