英伟达Senior DPU Test Development Engineer, SDET

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, 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 (SOC/ASAP/VDPA/VFE/VirtIO) • 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. • Assist AE team to repro customer issue locally.

We are looking for someone to be passionate about quality assurance. You’ll collaborate with multi-functional groups. Senior SWQA Test Development Engineers at NVIDIA aren't only manual testers, you write scripts to automate testing or build tools for QA team, so we can improve productivities or optimize test plan. We'd like to see your ability to identify weak spots and constantly craft better and creative test plans to break software and identify potential issues. You'll have a huge impact on the quality of NVIDIA's enterprise product. What you’ll be doing: • Utilizing AI-powered tools to enhance QA efficiency, including automating test case generation, defect detection, and regression testing. • Implementing AI-driven solutions to optimize test coverage and identify high-risk areas in software systems. • Collaborating with cross-functional teams to adopt AI tools that improve workflow automation and reduce manual effort. • Work closely with multi-functional teams to understand the test requirements and take ownership of product quality. • Develop test plans, design test cases, complete testing via automation and/or manually and compose test reports. • Build and maintain our complicated test environments. • Manage bug lifecycle and co-work with inter-groups to drive for solutions. • You will assist in the architecture, crafting and implementing of SWQA test frameworks. • Report bugs found during execution, assist with reproduction and debugs to understand root cause, verify bug fixes provided by R&D team, raise if not fixed. • Experience in using AI development tools. Adept at creating detailed test cases, automating them, increasing code coverage, identifying valid bugs early on, and solving these bugs swiftly.

• Contribute to design review and product features requirements under the whole Ethernet/ NIC/DPU/Switch portfolio. Design and build setup topologies with an emphasis on an emulation of customer large scale / complex environments. • Collaborating closely with multi-functional teams, including hardware engineers, software developers, and domain experts, to deliver optimized solutions that meet the demanding requirements of AI workloads. • Design, mentorship for testing automation team to implement tests. Generate comprehensive test reports during release execution procedure, assist with reproduction and debugs complex customer use cases, with determination of the issue root cause, be an engineering PIC for the full verification cycles of the customer use cases. • Complete end-to-end test scenarios in different scopes: Regression, Performance, Functional and Scale; Report the progress of testing and provide summary reports of testing activity. • Profiling, Benchmarking, and Analyzing Deep Learning models to identify areas for optimization and improvement in terms of performance, efficiency, and accuracy, with a strong emphasis on networking aspects. • Providing insights and recommendations based on the analysis of large-scale training results, specifically focusing on networking bottlenecks and optimizations, to improve model outcomes and achieve business objectives.

We are now looking for a Senior Solutions Architect, an outstanding engineer able to engage with developers, researchers, and decision makers. We need individuals who can use AI to improve system efficiency and develop close relationships with our industry customers, making NVIDIA a great part of end-user solutions.NVIDIA is the world leader in GPU accelerated computing and is looking for Solution Architects to engage our customers. The Senior Solution Architect will work closely with the industry customers in our China region - establishing relationships, solving problems with their engineering teams, and helping them to build a successful NVIDIA practice. If interested, do not hesitate to apply online, we are exciting to talk with you! What you’ll be doing: • Presenting NVIDIA’s full stack Artificial Intelligence solutions, and end to end platform technology to customers and partners. With in-depth hands-on engagements with customers or NVIDIA partners on complicated Datacenter projects. • Assist field business development in guiding the customer through the sales process for NVIDIA solution. • Understand and analyze customer requirements, support the solution design and development of applications. • Team work across the company to guide the direction of accelerated computing, working with software, research, and product teams. • Document the learnings to guide others. This can vary from making targeted training for customers and other Solutions Architects, giving nice hands-on demos, writing whitepapers, blogs, and wiki articles, recording short videos, to simply working through hard problems with a partner on a whiteboard.