Senior AI/ML Systems Automation Engineer

Amazon Web Services (AWS); Cupertino (CA); On-site; USD 174,000 - 235,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Web Services, Inc. seeks an experienced engineer to own end-to-end health of AI/ML accelerator fleets. You will build automation that prevents failures, correlate telemetry, and drive proactive diagnostics across PCIe, Linux drivers, and GPU subsystems.

You will design predictive failure detection, develop monitoring dashboards, and work across hardware, firmware, and software teams to improve fleet reliability at scale.

Qualifications

• Bachelor's degree in CS/CE/EE or equivalent work experience.
• 6+ years of professional software development experience.
• 6+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience.

Responsibilities

• Build and own the automation infrastructure for accelerator fleet health at a large scale of servers, driving toward zero-touch operations that detect, diagnose, triage, and remediate faults without human intervention.
• Design and develop test frameworks, test coverage strategies, and diagnostic tooling to validate hardware functionality, detect faults, and ensure qualification coverage across the platform lifecycle.
• Design predictive failure detection using telemetry, sensor data, error trending, and log correlation to identify degrading components before customer impact.
• Develop monitoring dashboards and alerting for real-time fleet health visibility across manufacturing, lab, and production environments.

Skills

C++

Python

Linux

System design

Kernel debugging

Education

Bachelor's degree in CS/CE/EE or equivalent

Tools

Linux drivers

PCIe topology

GPU debugging

Job description

Amazon Web Services, Inc. seeks an experienced engineer to own end-to-end health of AI/ML accelerator fleets. You will build automation that prevents failures, correlate telemetry, and drive proactive diagnostics across PCIe, Linux drivers, and GPU subsystems.

You will design predictive failure detection, develop monitoring dashboards, and work across hardware, firmware, and software teams to improve fleet reliability at scale.