AI Computing Software Development Engineer, TensorRT-LLM

We are now looking for a Software Development Engineer for LLM inference!

NVIDIA is hiring software engineers for its TensorRT-LLM team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning-powered AI, enabling breakthroughs in areas like LLM, Generative AI, and Agentic AI. Become part of the group building the inference software which will be used across our product lines! The ability to work on a fast-paced delivery-focused team is required and excellent interpersonal skills are a must.

Responsibilities:

• Craft and develop robust inference software that can be scaled to multiple platforms for functionality and performance
• Performance analysis and optimization for Large Language Model (LLM) inference
• Closely follow academic and industrial developments in the field of artificial intelligence and feature update TensorRT-LLM
• Implement kernels and runtime features to support new LLM models and inference algorithms
• Provide feedback into the architecture and hardware design and development
• Collaborate across the company to guide the direction of deep learning inference, working with software, research and product teams

Requirements:

• Master or higher degree in Computer Engineering, Computer Science, Applied Mathematics or related computing focused degree (or equivalent experience)
• 3+ years of relevant software development experience
• Excellent Python programming skills, software design, and software engineering skills
• Awareness of the latest developments in LLM architectures and LLM inference techniques
• Experience working with deep learning frameworks like PyTorch and HuggingFace
• Proactive and able to work without supervision
• Excellent written and oral communication skills in English

Preferred Qualifications:

• Prior experience with a LLM inference framework (TensorRT-LLM, SGLang, vLLM, lamma.cpp, MLC-LLM, etc.) or a DL compiler in inference, deployment, algorithms, or implementation
• Good understanding about the underlying operations inside the LLM inference frameworks or LLM inference end-to-end workflow
• Experience in performance modeling, profiling, debugging, and code optimization of a DL/HPC/high-performance application
• Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design
• Architectural knowledge of CPU and GPU
• GPU programming experience (CUDA or OpenCL)