NVIDIA is developing processor and system architectures that accelerate deep learning on edge devices, workstations, and data center GPUs for a variety of applications including automotive, robotics, large language models and AI generative models. We are looking for an expert deep learning system performance architect to join our deep learning modelling, performance optimization, projections, and analysis effort. In this position, you will have the chance to optimize deep learning hardware and software architecture and make the significant impact in a dynamic technology focused companyWhat you’ll be doing:Benchmark and analyze performance of various machine learning/deep learning workloads across GPU- and NPU-based architecturesBuild and validate performance models, and deliver performance projections and insights for deep learning (LLM/GenAI) workloads on emerging architecturesIdentify architecture, software and system performance bottlenecks and propose actionable optimizationsExplore and evaluate new software/hardware capabilities and translate them into measureable application gainsLeverage AI agents to accelerate performance investigation and engineering workflowsWhat we need to see:BSc. MS or PhD in relevant discipline (CS, EE, Math, etc.,)3+ years of working experience in relevant directions will be a plusFamiliar with GPU or Accelerator-based deep learning platform and software stackA strong background in computer architectureFamiliar with LLM or generative AI deep learning algorithms and kernel optimizationsExperience in system architecture design and performance optimizationFamiliar with machine learning and deep learning frameworksHands-on experience using AI agents to assist daily engineering work