Optical Engineering AI and Data Analytics Intern

We are the independent measurement engine for Meta's MR hardware. Every optical claim a headset makes — how sharp it looks, whether the colour is right, whether the two eyes fuse comfortably — is something our team measures and signs off on before the product ships.That measurement happens across roughly 80 instruments and factory stations spread over contract manufacturers in Asia, display vendors, and labs in Sunnyvale and Redmond. Those stations generate about 1.3 billion rows of test data, which flow through a pipeline we own and used across the org.The physics is interesting, but the bottleneck is not physics. It is data. Measurements that never reach the pipeline cannot be acted on, and today a large fraction of our upstream quality data never does. That is the problem this internship is pointed at.This is a 12 week internship.

Optical Engineering AI and Data Analytics Intern Responsibilities:

• Upstream Data Ingestion: Build automated ingestion paths and pipeline schemas to integrate previously offline lab and bench measurement data.
• Tool Calibration AI Agent: Develop an AI agent and system of record to track instrument certification, trigger automated maintenance alerts, and coordinate service scheduling.
• Production Test Analytics: Implement automated analytics layers for measurement system analysis (Gauge R&R), station-to-station correlation, and drift detection across large-scale production test data.

Minimum Qualifications:

• Currently pursuing a BS, MS, or PhD in Computer Science, Data Science, Statistics, Electrical Engineering, or a related field
• Proficiency in Python or TypeScript/JavaScript, and comfort learning the other
• Working knowledge of SQL and experience querying a relational or columnar data store
• Foundation in statistics and data modeling: distributions, hypothesis testing, regression, and fitting and judging a model against held-out data
• Experience building something other people used, such as a tool, pipeline, dashboard, model or library. Coursework counts if the artifact was real
• Able to explain a technical result, and how confident you are in it, to someone who does not share your background
• Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment
• Intent to return to full-time degree program after completion of the internship

Preferred Qualifications:

• Predictive modeling and time-series analysis: forecasting, trend and change-point detection, anomaly or drift detection, and back-testing a model before trusting it
• Statistical process control and measurement systems analysis: Cpk, control charts, Gauge R&R, station-to-station correlation
• Data modeling and pipelines: designing warehouse schemas, and distributed processing (Spark, Presto, Hive or equivalent) with ETL / pipeline orchestration
• Full-stack web development for data products: React / Next.js with TypeScript, server-side APIs (REST or GraphQL), and scheduled jobs
• Building with LLMs: agents, tool use, retrieval, or evaluation
• Testing and validating data products: automated checks that the numbers shown match the source data, and catching silent regressions
• Exposure to manufacturing, test, or instrumentation data and its usual problems: inconsistent station naming, missing metadata, silent schema drift
• An interest in optics or imaging. Useful, but genuinely not required

About Meta:

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at [email protected].

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.