Production Systems Engineering Intern

As part of Hardware Design and Release to Production (HDRTP) within Meta's Hardware Engineering organization, our team works across all NPI server projects (including cutting-edge AI training and inference hardware platforms) from early bring-up into large-scale production. We build the test automation, tooling, and diagnostics that validate GPU and accelerator platforms at scale, collaborating closely with internal teams and external vendors. This is a 12 week internship based in Menlo Park, CA.

Responsibilities

• Develop and extend test automation tooling across hardware servers and distributed systems to improve test coverage, reliability, and platform insight.
• Collaborate with cross-functional teams and external vendors to integrate feedback and validate system behavior against ground-truth datasets.
• Analyze large-scale internal and external datasets to identify gaps, enhance tool accuracy, and quantify performance improvements.
• Present technical findings to engineering stakeholders, document implementations, and hand off project deliverables at the conclusion of the internship.

Minimum Qualifications

• Currently enrolled in a full-time degree program in Computer Science, Computer Engineering, Electrical Engineering or a related field, with an expected graduation date after the internship.
• Programming experience in Python.
• Coursework or project experience in distributed systems, computer networks or computer architecture.
• Experience working in a Linux environment.
• Must be available to work onsite in Menlo Park for a 12-week internship in summer 2027.

Preferred Qualifications

• Experience with test automation frameworks, build systems or CI tooling.
• Familiarity with datacenter or cluster networking concepts such as topology, fabrics and interconnect.
• Experience querying, cleaning and analyzing structured datasets and data analysis tooling.
• Exposure to hardware validation, manufacturing test data or systems bring-up.
• Prior internship or research experience involving large-scale systems, telemetry or infrastructure tooling.