Senior Deep Learning Performance Architect - LPU

- 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

- 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

- Familiarity with GPU computing (CUDA or similar) and HPC (MPI, OpenMP) stack

- 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

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

Applications for this job will be accepted at least until July 26, 2026.