Packaging Mechanical Design Internship - Summer 2027

Mountain View, CAinternship

On Site

entry

H1B: yes

Lightmatter Lightmatter offers a Packaging Mechanical Design Internship for Summer 2027 to develop AI-enabled frameworks combining physics-based simulation and machine learning for package design. The role includes automating FEA and CFD processes and collaborating with engineers to refine design predictions.

Responsibilities

Build a flexible framework that links package design parameters (geometry, materials, process, thermal solution) to outputs such as thermal performance and warpage.
Develop and evaluate PINNs, other surrogate models, and reduced-order or analytical models for fast first-order predictions on new package concepts.
Automate FEA and CFD setup, execution, and post-processing in Python to generate parametric datasets. Train and validate models against high-fidelity simulation and hardware data, quantifying accuracy and uncertainty.
Plan and run physical DOEs (test setup, measurement, analysis) to build understanding of coupled thermal-structural-optical physics.
Partner with packaging, thermal, and thermo-mechanical engineers to define requirements and inputs/outputs, and adapt the framework to upcoming products.

Qualification

Coursework in heat transferExperience with thermal (IcepakCoursework in packagingExperience with PINNs

Required

Currently pursuing an MS or PhD in Mechanical Engineering or a related field.
Coursework in heat transfer, fluid mechanics, FEA, CFD, numerical methods, and solid or fracture mechanics.
Graduate research in multi-physics problems, with both modeling and experimental validation.
Experience with thermal (Icepak, Fluent, Flotherm) and structural (Ansys, Abaqus, COMSOL) simulation tools.
Proficiency in Python (or similar) for scripting, data processing, and simulation automation.
Curiosity and willingness to learn from the team.

Preferred

Graduate research in electronic or semiconductor packaging.
Familiarity with thermal-structural coupling, warpage, and package-level thermal management.
Coursework in packaging, numerical methods, or machine learning.
Experience with PINNs, scientific ML, or surrogate modeling of FEA/CFD data using PyTorch, TensorFlow, or JAX.
Interest in photonics and co-packaged optics.

Benefits

Dental
Vision
Equity/RSU
Parental Leave
Life Insurance

Company

Lightmatter

View company page

Source: greenhouse

Active within the past hour

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Must-Have Skills for This Role

Physics-based simulationMachine learningSurrogate modelsFEACFDPython

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