Reality Labs (RL) focuses on delivering Meta's vision through AI-first devices that leverage Mixed Reality (MR) and Augmented Reality (AR). The compute performance and power efficiency requirements of Mixed and Augmented Reality require custom silicon. Reality Labs Silicon team is driving the state of the art forward with highly integrated SoCs that leverage breakthrough work in computer vision, machine learning, mixed reality, graphics, displays, sensors, and new ways to map the human body. Our chips will enable AR & MR devices that blend our real and virtual worlds throughout the day. We are seeking Performance Architecture Interns with a background in Performance Modeling, Performance Simulation Methodologies, and/or Computer Architecture to improve our performance modeling collateral and use those models to guide the architecture of AR/MR silicon.
Requirements
- Experience with programming in C/C++ and scripting (Python)
- Experience in computer architecture (NoC, DRAM, Cache, MMU) through undergrad/grad course work
- Understanding of how to leverage performance modeling to support architectural exploration
- Understanding of hardware power, performance and area trade offs
- Experience in academic computer architecture simulators such as GEM5, SIMICS, etc
- Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as ISCA, ASPLOS, MICRO, HPCA, DAC, NOCS, ISPASS, PACT, etc
Responsibilities
- Carry out performance & power explorations of various architectural components using built performance models (exploration involves blocks such as NoC, DRAM, MMUs, etc)
- Develop AI-driven tools to identify and analyze performance outliers and extract actionable insights from simulation data
Other
- Currently has, or is in the process of obtaining, a Master's Degree in Computer Science, Electrical Engineering or related field
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment
- Intent to return to degree-program after the completion of the internship/co-op
- Currently has, or is in the process of obtaining, a PhD in Computer Science, Electrical Engineering or related field
- Experience working and communicating cross functionally in a team environment
