NVIDIA
generative AI
DeepLearningArchitect,LLMInference
Neural analysis suggests this role is
optimal for Entry candidates.
“Deep Learning Architect, LLM Inference at NVIDIA. Skills: Deep Learning Architect, LLM Inference, GPU hardware and software performance optimization, inference server performance optimization, PyTorch, TRT-LLM, vLLM, SGLang, profiling, compiler optimizations. workload characterization of the latest LLMs and inference servers. ensure NVIDIA maintains its leadership position in inference server performance optimization”
Industry & Context.
identifying performance bottlenecks
What They're Looking For.
Must Have
Master's or PhD degree in Computer Science, Computer Engineering, related fields, or equivalent experience, Relevant software development experience, Detailed knowledge of deep learning inference serving, PyTorch programming, profiling, compiler optimizations, Experience developing client server LLM applications with OpenAI API or MCP, identifying performance bottlenecks, Solid understanding of CPU and GPU microarchitecture and performance characteristics, Experience with complex software projects like frameworks, compilers, or operating systems, Demonstrated proficiency with the latest AI coding agents like Claude Code, Codex, and Cursor, Excellent written and verbal communication skills, ability to work independently and collaboratively in a fast-paced environment
Nice to Have
Demonstrate a drive to continuously improve software and hardware performance, Showcase examples of novel use cases for agentic AI tools in the workplace, Experience with databases and visualization tools
What You'll Do.
workload characterization of the latest LLMs and inference servers
ensure NVIDIA maintains its leadership position in inference server performance optimization
build engaging content
including blog posts and updates to InferenceX
highlight NVIDIA's outstanding inference achievements
establish standard benchmarking methodologies
develop a constantly evolving inference performance data results website
invent E2E profiling and analysis tools
contribute to deep learning software projects
drive advancements in the field
verify that new GPU product launches produce industry leading performance
guide the direction of inference serving
ensure best-in-class performance
use the latest coding agents and inference technology to improve team efficiency
How You'll Work.
Team & Collaboration
Join forces with the performance marketing team; Collaborate with engineers from AI startup companies; Collaborate across the company to guide the direction of inference serving; working with software, research, and product teams
Communication Scope
Excellent written and verbal communication skills
Full Job Description
We are now looking for a Deep Learning Architect, LLM Inference! NVIDIA is at the forefront of the generative AI revolution. The Inference Benchmarking (IB) team specifically focuses on inference server performance optimization for Large Language Models (LLMs). If you're passionate about pushing the boundaries of GPU hardware and software performance and understand terms like disaggregated serving, data parallel attention, MoE, Qwen3.5, DeepSeek, GPT-OSS, then this is a great role for you! **What you 'll be doing:** * You will do workload characterization of the latest LLMs and inference servers like vLLM, SGLang and TRT-LLM to ensure NVIDIA maintains its leadership position. * Join forces with the performance marketing team to build engaging content, including blog posts and updates to InferenceX to highlight NVIDIA's outstanding inference achievements. * Collaborate with engineers from AI startup companies to establish standard benchmarking methodologies. * Develop a constantly evolving inference performance data results website. * Invent E2E profiling and analysis tools that you will use to keep up with the rapid pace of Generative AI. * Contribute to deep learning software projects, such as PyTorch, TRT-LLM, vLLM, and SGLang to drive advancements in the field. * Verify that new GPU product launches produce industry leading performance. * Collaborate across the company to guide the direction of inference serving, working with software, research, and product teams to ensure best-in-class performance. * Use the latest coding agents and inference technology to improve team efficiency. **What we need to see:** * Master's or PhD degree in Computer Science, Computer Engineering, related fields, or equivalent experience. * Relevant software development experience. * Detailed knowledge of deep learning inference serving, PyTorch programming, profiling, and compiler optimizations. * Experience developing client server LLM applications with OpenAI API or MCP and identifyin
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