Platform Application Engineer, Cloud AI Infrastructure

What you'll do

• Diagnose customer issues and develop investigation tools to improve productivity on AI/ML infrastructure.
• Debug hardware and silicon issues, reproduce problems, determine root causes, and drive permanent improvements.
• Collaborate with Product, Quality, Engineering, and SRE teams to resolve complex deployment and operational obstacles.

What they ask for

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

Nice to have

• Experience with distributed systems and AI/ML computing hardware, including GPUs or other accelerators.
• Familiarity with Kubernetes or Slurm, systems automation, ML frameworks, and memory and high-speed IO technologies.

Pay

$159000 - $230000 USD (base salary)

Tools

CPU, dGPU, TPU, Linux/Unix, Kubernetes, Slurm, TensorFlow, PyTorch

AI focus

Troubleshoots AI/ML infrastructure and computing hardware, investigates AI/ML workloads, and supports understanding of the training and inference lifecycle.