Summary:
Reality Labs' Systems Engineering team shapes the hardware architecture of future devices, from VR/MR headsets to AI wearables. As an intern on the team, you'll help turn user experiences and workloads into quantitative hardware requirements across compute, memory, storage, power, and thermal, and contribute to the trade studies that drive silicon and platform decisions. You'll be paired with a mentor and own a scoped project that lands in a real platform definition.This is a 12 week internship.
Required Skills:
Hardware Systems Architecture Intern, Performance & Workload Analysis Responsibilities:
- Translate target use cases into hardware requirements - budgeting compute, memory bandwidth, storage throughput, power, and thermal for experiences such as mixed-reality passthrough, always-on AI assistant, and camera capture
- Contribute to architecture trade studies comparing SoC, memory, storage, and ISP options against performance, power, thermal, cost, and form-factor limits, using analytical models (e.g. roofline, bandwidth and power budgets) validated against measurements
- Measure platform behavior under load at the system level using power-rail instrumentation, thermal chambers, and hardware performance counters, and use the data to calibrate models
- Identify where performance is capped by hardware - memory bandwidth, power delivery, thermal headroom, I/O - rather than software
- Characterize how requirements shift across product classes, from a tethered or high-power headset to a battery-limited wearable
- Present findings to silicon, hardware, and product leads, and document results so they can feed into supplier evaluations and next-generation platform definitions
Minimum Qualifications:
Minimum Qualifications:
- Currently pursuing a Master's degree or higher in Electrical Engineering, Computer Engineering, or a related field
- Coursework or research experience in computer architecture, SoC design, or embedded systems, including memory hierarchy, interconnects, and power management
- Experience with quantitative modeling and data analysis in C++, Python, or MATLAB
- Intent to return to full-time degree program after completion of the internship
- Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
Preferred Qualifications:
Preferred Qualifications:
- Currently pursuing a PhD in Electrical Engineering, Computer Engineering, or a related field
- Research or project experience in performance and power modeling, workload characterization, or architectural simulation
- Hands-on experience with system-level measurement: power-rail instrumentation, thermal characterization, or hardware performance counters and profiling tools
- Familiarity with mobile or embedded SoC platforms, or with AR/VR, camera/ISP, or on-device ML workloads
- Experience communicating quantitative analysis to cross-functional engineering partners
Public Compensation:
$6,688/month to $11,880/month + benefits
Industry: Internet
Equal Opportunity:
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 accommodations-ext@meta.com.