Senior Platform Application Engineer, Cloud AI Infrastructure
Kirkland, WA, USA +1 · Senior · Full-time · Posted Oct 28, 2026
- Location
- Kirkland, WA, USA
Sunnyvale, CA, USA - Experience
- 6 years in technical infrastructure and CPU, dGPU, or TPU debug/validation; 5 years in hardware debug.
- Education
- Bachelor's degree in Computer Science, Management Information Systems, or another technical field, or equivalent practical experience.
About the job
Diagnoses and resolves customer issues in AI/ML infrastructure by debugging hardware and platform systems, identifying root causes, and driving lasting product improvements.
What you'll do
- Diagnose customer problems and develop investigation tools to improve AI/ML infrastructure support.
- Debug platform hardware and silicon issues, determine root causes, and drive permanent improvements with product, quality, engineering, and SRE teams.
- Troubleshoot AI/ML workloads and hardware architectures, and advise internal stakeholders on complex deployment and operational issues.
What they ask for
- 6 years of experience with technical infrastructure deployment, maintenance, troubleshooting, quality, and reliability.
- 6 years of CPU, dGPU, or TPU debug or validation experience.
- 5 years of hardware debug experience, such as silicon or platform debug, IO interface, or memory analysis.
- Experience debugging across the hardware/software stack and with Linux/Unix systems on enterprise-grade server infrastructure.
Nice to have
- Experience with AI/ML computing hardware, distributed systems, automation, ML frameworks, or containerization and orchestration technologies.
- Understanding of memory and high-speed IO technologies.
Pay
$188000 - $274000 (USD) base salary
Tools
CPU, dGPU, TPU, Linux/Unix, TensorFlow, PyTorch, Kubernetes, Slurm
AI focus
Supports AI/ML infrastructure by debugging computing hardware and workloads, building diagnostic tools, and troubleshooting training and inference environments.
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