英伟达AI Computing Software Development Engineer, TensorRT - New College Graduate 2026

• Craft and develop robust inferencing software that can be scaled to multiple platforms for functionality and performance • Performance analysis, optimization and tuning • Closely follow academic developments in the field of artificial intelligence and feature update TensorRT-LLM • Provide feedback into the architecture and hardware design and development • Collaborate across the company to guide the direction of machine learning inferencing, working with software, research and product teams • Publish key results in scientific conferences

NVIDIA has continuously reinvented itself over two decades. NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.This is our life’s work — to amplify human imagination and intelligence. AI becomes more and more important in Auto Driving and AI City. NVIDIA is at the forefront of the Auto Driving and AI City revolution and providing powerful solutions for them. All these solutions are based on GPU-accelerated libraries, such as CUDA, TensorRT and V/LLM inference framework etc. Now, we are now looking for an LLM inference framework developer engineer based in Shanghai. What you’ll be doing :• Craft and develop robust inferencing software that can be scaled to multiple platforms for functionality and performance • Performance analysis, optimization and tuning • Closely follow academic developments in the field of artificial intelligence and feature update • Collaborate across the company to guide the direction of machine learning inferencing, working with software, research and product teams

• Define the end-to-end technical architecture for the NIM Factory, from container build systems and CI/CD to Kubernetes deployment patterns and runtime optimization. • Drive technical strategy and roadmap, making high-impact decisions on frameworks, technologies, and standards that empower dozens of engineering teams. • Architect and influence the design of workflow orchestration systems that underpin the NIM factory. • Coach and mentor senior engineers across the organization, fostering a culture of technical excellence, innovation, and knowledge sharing. • Champion best practices in software development, including API design, automation, observability, and secure supply chain management. • Collaborate with leadership across research, backend, SRE, and product to align technical vision with product goals and influence technical roadmaps.

NVIDIA is the world leader in GPU Computing. We are passionate about four markets: Gaming, Automotive, Enterprise Graphics and HPC/Cloud Datacenters; in addition to our traditional OEM business. We are well positioned as the ‘AI Computing Company’, and our GPUs are the brains powering modern Deep Learning software frameworks, accelerated analytics, big data, modern data centers, smart cities, and driving autonomous vehicles. We have some of the most brilliant and talented people in the world working for us. If you are talented, bright, driven and if working with smart technical people across countries sounds interesting, this job is for you. Our team is mainly focusing on CUDA automation testing, CUDA Safety and CUDA test development areas, and we are now looking for a Senior CUDA Test Development Software Engineer. What you’ll be doing: • Design and Implement unit, integration, and API tests for CUDA driver and library • Design and implement tests for new features of CUDA driver and library • Automate CUDA tests, design test plan and enable them in automation testing infrastructure • Triage test results, isolate test failures and improve test coverage