Senior DL Inference Engineer — GPU-Optimized AI at Scale

NVIDIA Corporation; Netherlands; Remote; EUR 120,000 - 180,000; Full time

Job summary

NVIDIA seeks a Senior Software Engineer specializing in Deep Learning Inference for our growing team. You will design, build, and optimize the GPU-accelerated software that powers today’s AI applications, with focus on SGLang and vLLM.

You will collaborate across frameworks and libraries, deliver performance improvements for state-of-the-art models on datacenter GPUs and edge devices, and contribute to NVIDIA’s inference ecosystem including CUDA kernels and multi-GPU communication tools.

Qualifications

• Masters or PhD or equivalent experience in Computer Engineering, Computer Science, EECS or AI.
• 5+ years of relevant software development experience.
• Excellent C/C++ programming and software design skills.
• SW Agile skills are helpful; Python experience is a plus.
• Prior experience with training, deploying or optimizing the inference of DL models in production is a plus.
• Background with performance modeling, profiling, debugging and code optimization or architectural knowledge of CPU and GPU is a plus.

Responsibilities

• Performance optimization and tuning of DL models in domains such as LLM, Multimodal and Generative AI.
• Scale performance of DL models across architectures and NVIDIA accelerators.
• Contribute features and code to NVIDIA’s inference libraries, vLLM and SGLang, FlashInfer and LLM software solutions.
• Work with cross-collaborative teams across frameworks, NVIDIA libraries and inference optimization innovative solutions.

Skills

C/C++ programming

Python

Software design

Agile

Education

Master's/PhD in Computer Science/Engineering/AI

Tools

CUDA

CUTLASS

NCCL

vLLM

SGLang

OAI Triton

Job description

NVIDIA seeks a Senior Software Engineer specializing in Deep Learning Inference for our growing team. You will design, build, and optimize the GPU-accelerated software that powers today’s AI applications, with focus on SGLang and vLLM.

You will collaborate across frameworks and libraries, deliver performance improvements for state-of-the-art models on datacenter GPUs and edge devices, and contribute to NVIDIA’s inference ecosystem including CUDA kernels and multi-GPU communication tools.