Sr. Solution Architect
Indexed description
Lenovo is a US$83 billion revenue global technology powerhouse, ranked #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).
This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub.
Key Responsibilities
- Design and develop AI rack and cluster architectures covering GPU-based compute, network, and storage systems to form complete datacenter AI infrastructure solutions.
- Design and develop methodologies, processes, software frameworks and tools for AI cluster deployment and end-to-end performance evaluation and tuning.
- Design and develop hardware and software product features that improve AI cluster solutions in performance, manageability, serviceability, and so forth.
- Collaborate with cross-functional teams and contribute to business projects and customer engagements.
- BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or other related fields.
- 8+ years of experience in design and implementation of datacenter hardware and software systems, with expertise in at least one of the following areas: server, network, storage, performance benchmarking.
- Strong programming skills (e.g., C/C++, Python, Go, shell scripting).
- Understanding of Machine Learning and Deep Learning principles.
- Experience with Machine Learning frameworks such as PyTorch, LangChain, LangGraph, Autogen, etc.
- Excellent communication and leadership skills.
- Ability to learn new technologies and concepts quickly.
- Innovative mindset with the ability to think outside the box.
- PhD in Computer Science or Computer Engineering.
- Experience with AI infrastructure solutions in production environments.
- Experience with AI hardware and software stack (e.g., CPU, GPU, network switch, ML platforms, libraries, runtimes).
- Ability to innovate and publish at top conferences.
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