英伟达Solution Architect – Accelerated Computing Libraries
社招全职地点:北京 | 上海状态:招聘
工作描述
任职要求 NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC, GAMING. Our SA team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers, focusing on defining and solving computational challenges in LLM inference and training acceleration, as well as network communication and data transfer optimization. What You’ll Be Doing: • Drive the adoption of key NVIDIA AI and accelerated computing libraries across multiple industries by working closely with customers’ technical teams, local field teams, and global product teams. • Deeply understand customers’ workloads and requirements, and map them to NVIDIA libraries, identifying functional, performance, and usability gaps. • Design and validate solutions using NVIDIA libraries (e.g., for inference, training, data processing, and simulation), including PoCs, benchmarks, and best-practice reference designs. • Collaborate with NVIDIA product and engineering teams to prioritize and close key gaps through feature requests, performance tuning, and roadmap feedback, turning customer needs into concrete product improvements. • Build and maintain technical assets (sample code, reference implementations, design …
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包括英文材料
HPC+
https://www.ibm.com/think/topics/hpc
HPC is a technology that uses clusters of powerful processors that work in parallel to process massive, multidimensional data sets and solve complex problems at extremely high speeds.
大模型+
https://www.youtube.com/watch?v=xZDB1naRUlk
You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.
https://www.youtube.com/watch?v=zjkBMFhNj_g
Go+
https://www.youtube.com/watch?v=8uiZC0l4Ajw
学习Golang的完整教程!从开始到结束不到一个小时,包括如何在Go中构建API的完整演示。没有多余的内容,只有你需要知道的知识。
还有更多 •••
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