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 markets include gaming, automotive, professional vision, HPC, datacenters and networking in addition to our traditional OEM business. NVIDIA is also well positioned as the ‘AI Computing Company’, and NVIDIA GPUs are the brains powering modern Deep Learning software frameworks, accelerated analytics, modern data centers, and driving autonomous vehicles. We have some of the most experienced and dedicated people in the world working for us. If you are dedicated, forward-thinking, and if working with hard-working technical people across countries sounds exciting, this job is for you.We are now looking for a Software QA Test Development Engineer Intern, you will collaborate with multi-functional groups. SWQA test developer engineer at NVIDIA is responsible for test planning, execution, and reporting, you will also write scripts to automate testing, design and develop tools for QA team, or develop integration tests for validation, so QA engineer can improve productivity or optimize test plan. As a SWQA test developer, you must identify weak spots and constantly design better and creative test plans to break software and identify potential issues. You will have a huge impact on the quality of NVIDIA's products. What you’ll be doing: • Be responsible for executing test cases to validate NVIDIA enterprise offerings, such as BlueField DPU/NIC • Automate test cases and maintain the automation scripts. • Work with development teams to triage issues, root cause analysis, verify fixes, define new tests, and improve test plans.