Deep Learning Systems Software Engineer

Role Overview: As a senior engineer at NVIDIA, you will play a crucial role in the optimization of deep learning workloads on cutting-edge hardware and software platforms. Your primary responsibility will be to understand, analyze, and profile these workloads to achieve peak performance. By building automated tools for workload analysis and optimization, you will contribute to enhancing the efficiency of GPU utilization and cloud application performance across diverse GPU architectures. Key Responsibilities: - Collaborate with cross-functional teams to identify bottlenecks and inefficiencies in application code, proposing optimizations to drive end-to-end platform optimization. - Design and implement performance benchmarks and testing methodologies to evaluate application performance accurately. Qualifications Required: - Hold a Master's degree in CS, EE, or CSEE, or possess equivalent experience. - At least 5 years of experience in application performance engineering, with a background in deep learning model architectures. - Proficiency in tools such as NVIDIA NSight and Intel VTune, and a deep understanding of computer architecture and GPU fundamentals. - Proficiency in Python and C/C++ for analyzing and optimizing application code effectively. - Strong fundamentals in algorithms and GPU programming experience (CUDA or OpenCL) will be highly beneficial. - Hands-on experience in performance optimization and benchmarking on large-scale distributed systems. - Familiarity with NVIDIA's server and software ecosystem, and expertise in storage systems, Linux file systems, and RDMA networking will be advantageous.,