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About MindbeamWe are building the next-generation AI infrastructure for open source and enterprise. Our work is deeply research-oriented and passionate about developing ground-breaking innovations to take state-of-the-art AI applications to the next level.MissionPush the boundaries of performance by developing custom kernels and low-level optimizations for next-generation AI workloads.Role ExpectationsDesign and implement custom GPU/accelerator kernels to maximize performance.Profile, benchmark, and optimize critical ML workloads.Collaborate with researchers to translate algorithmic advances into efficient, production-ready code.Stay current with hardware advancements (CUDA, ROCm, TPU) to inform kernel design.Document and share best practices for low-level optimization.BackgroundBachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, or related field—or equivalent experience.2+ years of experience in GPU programming, parallel computing, or systems-level optimization.Strong coding skills in C++, CUDA, or similar languages.Familiarity with ML frameworks and their low-level backends.Experience optimizing workloads for distributed and heterogeneous compute environments.Comfort with profiling tools and performance diagnostics.About YouYou are detail-oriented, performance-obsessed, and excited by the challenge of squeezing out every ounce of compute efficiency. You enjoy working at the intersection of algorithms and hardware, and you thrive in a collaborative environment where bold ideas are encouraged.
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