Senior DL Inference Engineer — GPU-Accelerated AI at Scale

NVIDIA; United Kingdom; On-site; GBP 110,000 - 160,000; Full time

Benefits offered by this job

Competitive salaries

Extensive benefits package

Diversity & inclusion

Job summary

NVIDIA seeks a Senior Software Engineer specializing in Deep Learning Inference to design, build, and optimize GPU-accelerated software powering cutting-edge AI. You will contribute to SGLang, vLLM, and related DL frameworks, enhancing model serving across datacenter GPUs to edge accelerators.

You''ll collaborate across frameworks and NVIDIA libraries, focusing on performance modeling, profiling, and code optimization for state-of-the-art LLMs and Generative AI, using CUDA kernels, CUTLASS,

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; Python experience a plus.
• Experience with training, deploying, or optimizing inference of DL models in production is a plus.
• Background with performance modeling, profiling, debugging, and code optimization on CPU/GPU 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.
• Collaborate with cross-functional teams across frameworks, NVIDIA libraries and inference optimization innovations.

Skills

C/C++ programming

Python programming

Software design

Performance optimization

Agile

Education

Master's or PhD in a relevant field

Tools

SGLang

vLLM

CUTLASS

NCCL

CUDA kernels

OAI Triton

Job description

NVIDIA seeks a Senior Software Engineer specializing in Deep Learning Inference to design, build, and optimize GPU-accelerated software powering cutting-edge AI. You will contribute to SGLang, vLLM, and related DL frameworks, enhancing model serving across datacenter GPUs to edge accelerators.

You''ll collaborate across frameworks and NVIDIA libraries, focusing on performance modeling, profiling, and code optimization for state-of-the-art LLMs and Generative AI, using CUDA kernels, CUTLASS,