Fleet AI Production Engineer: Hardware & Automation

Meta; Menlo Park (CA); On-site; USD 173,000 - 245,000; Full time

Benefits offered by this job

Bonus

Equity

Benefits

Job summary

Meta seeks an experienced Production Systems Engineer on the Fleet AI Systems team to drive hardware and software health testing across data centers. You will develop test suites, automation frameworks, and remedies for complex server ecosystems, partnering with hardware vendors, software engineers, and data center operations.

The role requires 8+ years in hardware server support, strong Linux scripting skills, and proven ability to diagnose system-level issues across the full stack.

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering or a related field, or equivalent practical experience.
• 8+ years of experience in hardware server system support and troubleshooting.
• Strong Linux background with scripting in Python or similar languages.

Responsibilities

• Drive interfacing with external vendors and internal teams to develop test suites for various architectures.
• Own experiments and tooling to detect and diagnose hardware/firmware/software health issues.
• Develop test frameworks for large-scale automation and post-production remediation.
• Troubleshoot, diagnose and root cause system failures across hardware and software.
• Document resolutions and communicate findings across stakeholders.

Skills

Linux

Python

Scripting

Hardware troubleshooting

System analysis

Education

Bachelor's degree in CS/CE or equivalent

Master's degree preferred

Job description

Meta seeks an experienced Production Systems Engineer on the Fleet AI Systems team to drive hardware and software health testing across data centers. You will develop test suites, automation frameworks, and remedies for complex server ecosystems, partnering with hardware vendors, software engineers, and data center operations.

The role requires 8+ years in hardware server support, strong Linux scripting skills, and proven ability to diagnose system-level issues across the full stack.