Deep Learning Performance Architect

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 company

What you’ll be doing:

• Benchmark and analyze performance of various machine learning/deep learning workloads across GPU- and NPU-based architectures

• Build and validate performance models, and deliver performance projections and insights for deep learning (LLM/GenAI) workloads on emerging architectures

• Identify architecture, software and system performance bottlenecks and propose actionable optimizations

• Explore and evaluate new software/hardware capabilities and translate them into measureable application gains

• Leverage AI agents to accelerate performance investigation and engineering workflows

What 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 plus

• Familiar with GPU or Accelerator-based deep learning platform and software stack

• A strong background in computer architecture

• Familiar with LLM or generative AI deep learning algorithms and kernel optimizations

• Experience in system architecture design and performance optimization

• Familiar with machine learning and deep learning frameworks

• Hands-on experience using AI agents to assist daily engineering work