[Remote] Senior Deep Learning Performance Architect - LPU

Note: The job is a remote job and is open to candidates in USA. NVIDIA is seeking a Senior Deep Learning Performance Architect to advance AI inference performance through hardware-software co-design. The role develops performance strategies and models, informs future GPU architecture, and collaborates with software, research, and product teams.

Responsibilities

• Design novel GPU and system architectures to advance the forefront of AI Inference performance and efficiency
• Construct, investigate, and test popular deep learning algorithms and applications
• Understand and analyze the relationship between hardware and software architectures as it influences future algorithms and applications
• Build efficient power and performance models of AI inference stack, while capturing minimal but significant information to guide next-gen HW architecture
• Collaborate across the company to guide the direction of AI, working with software, research, and product teams

Skills

• A MS or PhD in a relevant field (CS, EE, Math) or equivalent experience, with 5+ years of relevant experience
• Strong mathematical foundation in machine learning and deep learning
• Expert programming skills in C, C++, and/or Python
• Familiarity with GPU computing (CUDA or similar) and HPC (MPI, OpenMP) stack
• Strong knowledge and coursework in computer architecture
• Background with systems-level performance modeling, profiling, and analysis
• Experience in characterizing and modeling system-level performance, accomplishing comparison studies, and documenting and publishing results
• Background in improving AI Inference workloads by developing CUDA kernels or compilers for custom ASIC hardware

Benefits

• Equity

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