NVIDIA
AI
SeniorDLAlgorithmsEngineer-InferencePerformance
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior DL Algorithms Engineer - Inference Performance at NVIDIA. Skills: Deep Learning Algorithms, Inference Performance Optimization, GPU Architecture, LLM Optimization. Enable and optimize state-of-the-art open models (like Nemotron and Cosmos) on NVIDIA’s accelerated inference SW stack. Contribute new features, fix bugs and deliver production code to open-source frameworks like TRT-LLM, vLLM, SGLang, FlashInfer, etc.”
What You'll Achieve.
squeeze every last clock cycle out of Deep Learning workloads; achieve peak performance; push the boundaries of inference performance
Industry & Context.
performance analysis and optimization; Profile and analyze bottlenecks across the full inference stack
What They're Looking For.
Must Have
PhD in CS, EE or CSEE or equivalent experience, 3+ years of experience, background in deep learning and neural networks, in particular inference, Experience with performance profiling, analysis and optimization, especially for GPU-based applications, Proficient in PyTorch or equivalent frameworks for AI, or HPC-heavy application development, Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture
Nice to Have
Proven experience with processor and system-level performance optimization, Deep understanding of modern LLM/Diffusion architectures, fundamentals in algorithms, GPU programming experience (CUDA or OpenCL)
What You'll Do.
Enable and optimize state-of-the-art open models (like Nemotron and Cosmos) on NVIDIA’s accelerated inference SW stack
Contribute new features
fix bugs and deliver production code to open-source frameworks like TRT-LLM
Profile and analyze bottlenecks across the full inference stack to push the boundaries of inference performance
Benchmark state-of-the-art offerings and perform competitive analysis for NVIDIA’s SW/HW stack
Co-design with partner teams to develop the next generation of AI models and services
How You'll Work.
Team & Collaboration
Co-design with partner teams
Full Job Description
We are looking for a Senior DL Algorithms Engineer for LLM/Omni model optimizations! Seeking senior engineers who are mindful of performance analysis and optimization to help us squeeze every last clock cycle out of Deep Learning workloads. If you are unafraid to work across all layers of the hardware/software stack from GPU architecture to Deep Learning Framework to achieve peak performance, we want to hear from you! This role offers an opportunity to directly impact the hardware and software roadmap in a fast-growing technology company that leads the AI revolution. **What you will be doing:** * Enable and optimize state-of-the-art open models (like Nemotron and Cosmos) on NVIDIA’s accelerated inference SW stack. * Contribute new features, fix bugs and deliver production code to open-source frameworks like TRT-LLM, vLLM, SGLang, FlashInfer, etc. * Profile and analyze bottlenecks across the full inference stack to push the boundaries of inference performance. * Benchmark state-of-the-art offerings and perform competitive analysis for NVIDIA’s SW/HW stack. * Co-design with partner teams to develop the next generation of AI models and services. **What we want to see:** * PhD in CS, EE or CSEE or equivalent experience. * 3+ years of experience. * Strong background in deep learning and neural networks, in particular inference. * Experience with performance profiling, analysis and optimization, especially for GPU-based applications. * Proficient in PyTorch or equivalent frameworks for AI, or HPC-heavy application development. * Deep understanding of computer architecture, and familiarity with the fundamentals of GPU architecture. **Ways to stand out from the crowd:** * Proven experience with processor and system-level performance optimization. * Deep understanding of modern LLM/Diffusion architectures. * Strong fundamentals in algorithms. * GPU programming experience (CUDA or OpenCL) is a strong plus. Your base salary will be determined based on your location, experience
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