AI Performance Engineer

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.

Basic Qualifications

• BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or other related fields.
• at least 2 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).
• Excellent communication and leadership skills.
• Ability to learn new technologies and concepts quickly.
• Innovative mindset with the ability to think outside the box.

Preferred Qualifications:

• 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.