Senior DL Inference & Optimization Engineer

NL02 NVIDIA Dutch B.V. Incorporated; Netherlands; On-site; EUR 120,000 - 150,000; Full time

Job summary

NVIDIA seeks a Senior Software Engineer specializing in Deep Learning Inference for our growing team. As a key contributor, you will help design, build, and optimize the GPU-accelerated software that powers today’s most sophisticated AI applications.

Our team is responsible for developing and maintaining high-performance deep learning frameworks, including SGLang and vLLM, which are at the forefront of efficient large-scale model serving and inference.

Qualifications

• Master's degree or PhD in Computer Science, Computer Engineering, EECS, or AI.
• 5+ years of relevant software development experience.
• Excellent C/C++ programming and software design skills; 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 CPU/GPU optimization is a plus.

Responsibilities

• Performance optimization, analysis, and tuning of DL models in domains like 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 innovations.

Skills

C/C++ programming

Python programming

Software design

Agile

Education

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

Tools

SGLang

vLLM

CUTLASS

OAI Triton

NCCL

CUDA kernels

Job description

NVIDIA seeks a Senior Software Engineer specializing in Deep Learning Inference for our growing team. As a key contributor, you will help design, build, and optimize the GPU-accelerated software that powers today’s most sophisticated AI applications.

Our team is responsible for developing and maintaining high-performance deep learning frameworks, including SGLang and vLLM, which are at the forefront of efficient large-scale model serving and inference.