Deep Learning Performance Architect
NVIDIAJob Title
Deep Learning Performance Architect
Role Summary
Work on performance modelling, analysis, and optimization for deep learning (including LLM) workloads on current and next-generation NVIDIA hardware. The role partners with architecture, software, and product teams to influence processor and system design for inference performance and efficiency.
Experience Level
Mid-level — typically 5+ years of relevant industry experience.
Responsibilities
Analyze models and define measurable opportunities to improve DL inference performance across software and hardware.
- Analyze state-of-the-art deep learning networks (e.g., LLMs) and prototype performance optimizations.
- Develop analytical performance and efficiency models for DL algorithms and systems.
- Specify hardware/software configurations and metrics to evaluate performance, power, and accuracy for uni- and multi-processor setups.
- Collaborate with architecture, software, and product teams to guide next-generation HW/SW direction.
Requirements
Must-have technical experience and skills.
- 5+ years of relevant work experience in deep learning performance, systems, or architecture.
- Experience with popular AI models, including LLMs and AIGC models.
- Familiarity with deep learning software frameworks (e.g., PyTorch, JAX, TensorFlow, TensorRT).
- Practical knowledge of hardware architectures for deep learning workloads.
- Ability to prototype, measure, and communicate performance trade-offs across teams.
Education Requirements
BS, MS, or PhD in Computer Science, Electrical Engineering, Mathematics, or a related technical field, or equivalent practical experience.
About the Company
Company: NVIDIA
Headquarters: Santa Clara, California, USA
NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.
