MTS - HBM Thermal Integration Engineer

Micron•Richardson, TX

17h

About The Position

Micron Technology is seeking an experienced MTS - HBM Thermal Integration Engineer to optimize thermal performance for next-generation High Bandwidth Memory (HBM) products. The role is within the Heterogeneous Integration Group, which develops HBM solutions for next-generation AI and high-performance computing systems. It intersects thermal simulation, silicon characterization, process technology, package development, manufacturing, test engineering, and product integration. The engineer will drive thermal performance improvements across HBM design, processes, packaging, assembly, and testing. The role involves developing thermal learning and characterization plans, analyzing silicon and manufacturing data, and partnering with simulation teams to correlate predictive models with measured performance. The engineer will collaborate across wafer fabrication, package development, assembly, product engineering, and reliability teams, and lead data-driven investigations to resolve thermal challenges and improve product performance.

Requirements

PhD with at least 5 years of industry experience, or a master's degree with at least 10 years of industry experience, in Mechanical Engineering, Materials Science, Physics, Semiconductor Engineering, Electrical Engineering, or a related technical field.
Hands-on semiconductor product development experience in memory, logic, or advanced packaging technologies, with a background in at least one of Process Integration, Package Integration, Product Engineering, or Yield Engineering.
Working knowledge of thermal simulation methodologies and multiphysics modeling, including the ability to interpret simulation results and apply insights to silicon, package, and technology optimization.
Experience designing, executing, and analyzing structured experiments and DOE-based investigations.
Demonstrated ability to analyze large datasets, including inline metrology, characterization, manufacturing, and test data, to identify performance drivers and sources of variation.
Ability to leverage AI-enabled tools and workflows to analyze data, automate routine tasks, improve decision-making, and enhance work efficiency and quality.

Nice To Haves

Understanding of HBM, advanced semiconductor packaging, 2.5D/3D integration, TSV technologies, hybrid bonding, interposers, and heterogeneous integration.
Experience with thermal characterization and silicon validation techniques.
Experience analyzing inline metrology, manufacturing, assembly, and test datasets using statistical methods.
Knowledge of variation analysis, process optimization, and root-cause investigation methodologies.
Familiarity with thermal simulation tools such as Ansys, Abaqus, Icepak, FloTHERM, Star-CCM+, or equivalent.
Experience with Python, JMP, MATLAB, SQL, or similar data analysis environments.
Experience leading cross-functional technology development initiatives in the semiconductor industry.

Responsibilities

Drive thermal performance optimization across HBM products through design, process, packaging, assembly, and test improvements.
Develop and implement thermal learning plans, characterization strategies, and design-of-experiments (DOE).
Analyze silicon characterization, inline metrology, manufacturing, and test data to identify key drivers of thermal behavior and variation.
Partner with thermal simulation teams to improve correlation between predictive models and measured silicon performance.
Work with wafer fabrication, package development, assembly, product engineering, and reliability teams to resolve thermal challenges and enable product improvements.
Identify and implement opportunities to reduce thermal resistance, improve thermal consistency, and enhance product performance.
Drive cross-functional technical investigations and influence engineering decisions through data-driven analysis and structured problem solving.
Use AI-enabled tools and workflows to analyze data, automate routine tasks, improve decision-making, and enhance the efficiency and quality of assigned responsibilities.