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What you’ll be doing:
Develop innovative HW, DSP, GPU and system architectures to extend the state of the art in AI Inference performance and efficiency
Analyze and prototype key deep learning and data analytics algorithms and applications
Understand and analyze the interplay of hardware and software architectures on future algorithms and applications
Write efficient software for AI Inference, including CUDA kernels, framework level code, and application-level code
Collaborate across the company to guide the direction of AI, working with software, research, and product teams
What we need to see:
Recently completed a MS or PhD in Computer Science, Electrical Engineering, Math or related field (or equivalent experience)
Strong mathematical foundation in machine learning and deep learning
Expert programming skills in C, C++, or Python
Familiarity with GPU computing (CUDA or similar) and HPC (MPI, OpenMP)
Strong knowledge and coursework in computer architecture
Ways to stand out from the crowd:
Background with systems-level performance modeling, profiling, and analysis
Experience in characterizing and modeling system-level performance, executing comparison studies, and documenting and publishing results
Experience in optimizing AI Inference workloads with CUDA kernel development
You will also be eligible for equity and .
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