Mechanical Engineering Intern

Meta is seeking a graduate mechanical engineering student with a strong background in finite element analysis (FEA) to join our Accelerator Reference Design (ARD) team. ARD designs and delivers production-quality accelerator modules for Meta's custom AI silicon (MTIA), covering board design, power delivery, thermal-mechanical design and module management hardware. As the team grows its in-house design and simulation capabilities, this intern will run the structural simulations that guide the mechanical design of our high-power, liquid-cooled modules. You'll work closely with mechanical, thermal, packaging and electrical engineers.

Responsibilities

• Build, mesh and run structural FEA models in ANSYS of accelerator modules, PCBs and mechanical hardware such as stiffeners and cold plates.
• Simulate mounting and preload, assembly, gravity and handling loads to evaluate stress, strain and deflection against design criteria.
• Run warpage simulations at room and elevated temperatures for bare boards, populated boards and full assemblies.
• Run design-of-experiment and parametric studies (geometry, thickness, material) to support design trade-offs.
• Correlate simulation results with lab test data (e.g. shadow moiré, strain gauge) and refine models to improve accuracy.
• Document assumptions, boundary conditions and results in clear reports, and present findings and recommendations to the ARD team.

Qualifications

• Currently pursuing a Master's or PhD degree in Mechanical Engineering
• Hands-on experience with ANSYS (Mechanical or Workbench) for structural FEA, through coursework, research or projects
• Deep foundation in solid mechanics, strength of materials, and material behavior Experience with thermo-mechanical, warpage or composite/laminate (e.g. PCB) modeling
• Experience correlating simulation with physical test data
• Experience bringing ECAD/MCAD data into FEA models
• Experience with 3D CAD tools, Creo preferred and SolidWorks acceptable, for geometry cleanup and simplification
• Scripting or automation experience (e.g. Python, APDL) for parametric studies or post-processing
• Experienced analytical, technical writing and communication skills