Drimva

Micron

MTS - HBM Thermal Integration Engineer

Richardson, TX · Full-time · Posted Oct 15, 2026

Experience
PhD with 5+ years of industry experience, or Master’s degree with 10+ years of industry experience.
Education
PhD or Master’s degree in Mechanical Engineering, Materials Science, Physics, Semiconductor Engineering, Electrical Engineering, or a related technical field.

About the job

Optimizes thermal performance in next-generation HBM products by analyzing silicon and manufacturing data and coordinating improvements across design, process, packaging, assembly, and test.

What you'll do

  • Develop thermal learning plans, characterization strategies, and design-of-experiments to improve technology understanding.
  • Analyze characterization, metrology, manufacturing, and test data to identify thermal drivers and variation.
  • Partner across simulation, fabrication, packaging, assembly, product engineering, and reliability teams to resolve thermal challenges and improve products.

What they ask for

  • Hands-on semiconductor product development experience in memory, logic, or advanced packaging, with a background in Process Integration, Package Integration, Product Engineering, or Yield Engineering.
  • Working knowledge of thermal simulation methodologies and multiphysics modeling.
  • Experience designing, executing, and analyzing structured experiments and DOE investigations.
  • Ability to analyze large datasets, including metrology, characterization, manufacturing, and test data; use AI-enabled tools and workflows in assigned responsibilities.

Nice to have

  • Knowledge of HBM, advanced packaging, 2.5D/3D integration, TSV, hybrid bonding, interposers, or heterogeneous integration; thermal characterization experience.
  • Familiarity with simulation or data tools such as Ansys, Abaqus, Icepak, FloTHERM, Star-CCM+, Python, JMP, MATLAB, or SQL.

Tools

Ansys, Abaqus, Icepak, FloTHERM, Star-CCM+, Python, JMP, MATLAB

AI focus

Use AI-enabled tools and workflows to analyze data, automate routine tasks, improve decision-making, and enhance efficiency and quality.

Model-written summary · the original posting is authoritative

First seen Oct 16, 2026 · Last verified Nov 5, 2026 (UTC)