Manufacturing Test Engineering Intern, Field Requirements & Feedback
Generate a McCoy IQ challenge in 30 seconds.
See how candidates think and approach the work this role demands, before the phone screen. We'll build a video challenge from this posting, and you can edit or share it before it goes live.
Key details
Job Description
Reality Labs builds wearable devices that make it easier for people to connect with the ones they love. These devices are manufactured and tested at scale in factories worldwide. The Manufacturing Test Engineering (MTE) team develops the test strategies, test systems, and test coverage that ensure every device we ship is functional and meets its requirements. Today, product requirements, factory test coverage, and what customers actually experience in the field live in separate places. We want to connect them. As a Manufacturing Test Engineering Intern, you will help build a closed feedback loop that connects product requirements through to engineering test requirements, test readiness plans, and field outcomes such as customer reviews and failure analysis of early returned devices. The question you will help us answer is a fundamental one: in the factory, are we testing what customers actually need, not more and not less? This is a cross-functional, systems-level program role. You will work across multiple product programs, partner with product management, design, quality, and test engineering, and deliver a framework and analysis the team can keep using after your internship. This is a 12-week internship.
Responsibilities
Learn how Reality Labs products move from product requirements through design, manufacturing, and test, across multiple product categories (smart glasses, AR glasses, VR headsets, wrist wearables, and charging cases). Build a traceability framework linking product requirements (PRDs) to engineering test requirements, test coverage, and test readiness plans, and identify where requirements are untested, over-tested, or untraceable. Gather and analyze field data, including customer reviews and failure analysis of early returned devices, and map observed failures back to the test coverage that should have caught them. Identify coverage gaps (field failures our factory tests do not catch) and coverage excess (tests that add cost and cycle time without protecting a real customer requirement). Partner cross-functionally with product management, quality, reliability, design, and test engineering teams to validate findings and align on recommendations. Recommend and help implement a repeatable process for closing the loop from field outcomes back into test requirements for the next program. Present findings, analysis, and recommendations to the team and to engineering leadership.
Qualifications
Currently has, or is in the process of obtaining, a Bachelors or Masters in Systems Engineering, Industrial Engineering, Manufacturing Engineering, Engineering Management or related field Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment Experience structuring ambiguous, open-ended problems and driving them to a clear recommendation Experience with data analysis in Excel, Python, SQL or equivalent, including working with qualitative data such as customer feedback or failure reports Coursework, internship, or project experience in requirements management, systems engineering, or verification and validation Exposure to quality or reliability engineering concepts: root cause analysis, failure analysis, FMEA, 8D, statistical process control, yield and return-rate analysis Experience in a manufacturing, supply chain, or operations environment, including exposure to consumer electronics production Experience coordinating across multiple teams or stakeholders on a project with competing priorities Experience using AI tools to accelerate analysis, document review, or data synthesis
Interested in working for companies like this one?
Answer a McCoy challenge. Companies hiring in engineering see your response and reach out when they want to talk.
About 15 minutes to prepare and 5 minutes to record. Unlimited retakes and a teleprompter help you answer. No AI training, and you can delete your response anytime.
This isn't an application to Meta.
Audit details(provenance, verification trail, raw fields)
Core fields
meta:940553205402689Provenance
metaVerification trail
This posting hasn't been probed by our closure verifier yet. Stream C runs on a rolling schedule against postings approaching the close-decision threshold.
LLM enrichment
See how we measure for definitions, or our corrections log for known issues. Found something wrong? Flag a correction.
