Field Application Engineer, Cloud AI Infrastructure

What you'll do

• Manage on-call CPU- and TPU-based server and data center issues; diagnose and resolve customer problems and develop investigation tools.
• Troubleshoot and reproduce hardware and AI/ML infrastructure issues, identify root causes, and build tools for faster diagnosis.
• Advise customers and internal teams, and collaborate with Product, Quality, Engineering, and SRE teams to improve products and reliability.

What they ask for

• Bachelor's degree in Computer Science, Management Information Systems, a related technical field, or equivalent practical experience.
• 2 years of debug or validation experience with CPU, dGPU, or TPU.
• 2 years of experience with technical infrastructure deployment or maintenance, troubleshooting, quality, and reliability.
• 2 years of hardware debug experience; experience with Linux/Unix and troubleshooting across the hardware/software stack on enterprise-grade server infrastructure.

Nice to have

• Experience working directly with AI/ML computing hardware, including GPUs or other accelerators.
• Experience with systems automation and design/debug, vendors or customers, distributed systems, ML frameworks, or memory and high-speed IO technologies.

Pay

$132000 - $189000 (USD) base salary

Tools

CPU, dGPU, TPU, Linux/Unix, TensorFlow, PyTorch, SRE

AI focus

Supports AI/ML infrastructure by debugging CPU-, GPU-, and TPU-based hardware and understanding AI/ML workloads; develops tools to accelerate diagnosis.