如题,小组内部推荐,直达经理。
候选人不限背景,要求熟悉 Linux,熟悉 shell/python/c 其中 1 到 2 项。公司待遇好,非 996,可灵活选择在家办公。有意向者可发送简历到 jingxuan126@126.com ,有问题也可咨询,来信必复。
如果需要内推其他职位,可以自行官网搜索,将职位链接连同简历一起发送:
https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite以下是该职位介绍:
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, 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.
We are now looking for a Senior CUDA Test Development Software Engineer, you will be working under dynamic environment on different project assignments, all are with cutting edging technology and ultimately you’ll be responsible for NVIDIA’s compute software test planning, execution and reporting, you’ll drive product quality and deliver the best quality to customers worldwide.
What you’ll be doing:
Work closely with global cross-functional teams to understand the test requirements and take ownership of product quality.
Plan/design/execute/report/automate test plan/test case/test reports.
Manage bug lifecycle and co-work with inter-groups to drive for solutions
Automate test cases.
In-house repro and verify customer issues/fixes
What we need to see:
BS or higher degree or equivalent experience in CS/EE/CE or equivalent with 5+ years QA experience
Proficient Linux experience and shell/python programming skills
Rich experience in test cases development, tests automation and failure analysis
Good QA sense, knowledge and experience in software testing
Problem solving skills
Excellent communicator, both written and verbal
Good teamwork with ability to work independently
Passion to learn new hardcore technology
Ways to stand out from the crowd:
Experience working with NVIDIA GPU hardware is a strong plus
Background in parallel programming ideally CUDA/OpenCL is a plus
Experience with virtualization technologies like Docker, Kubernetes, Openstack
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