Description
We are now looking for a Senior Deep Learning Performance Architect to join our group of pioneers who enjoy pushing AI Inference performance boundaries. Our team focuses on ambitious hardware-software co-design to speed AI Inference workloads. This role gives an outstanding opportunity to develop world-class performance strategies, guide future GPU architecture decisions, and lead AI innovation.
As a Senior Deep Learning Performance Architect, you will design novel GPU and system architectures to advance the forefront of AI Inference performance and efficiency. You will construct, investigate, and test popular deep learning algorithms and applications, understanding and analysing the relationship between hardware and software architectures as it influences future algorithms and applications.
You will build efficient power and performance models of AI inference stack, while capturing minimal but significant information to guide next-gen HW architecture. You will collaborate across the company to guide the direction of AI, working with software, research, and product teams.
To succeed in this role, you will need a 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, and strong knowledge and coursework in computer architecture.
If you have a background with systems-level performance modelling, profiling, and analysis, experience in characterising and modelling system-level performance, accomplishing comparison studies, and documenting and publishing results, and a background in improving AI Inference workloads by developing CUDA kernels or compilers for custom ASIC hardware, you will stand out from the crowd.