[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 join their innovative team focused on enhancing AI Inference performance. This role involves designing cutting-edge GPU architectures, analyzing hardware-software relationships, and collaborating with various teams to drive AI advancements.
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
- You will also be eligible for equity and benefits.
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