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MTS - HBM Thermal Integration Engineer Richardson, Texas, Posted

Job in Richardson, Dallas County, Texas, 75080, USA
Listing for: Micron Technology, Inc.
Full Time position
Listed on 2026-10-18
Job specializations:
  • Engineering
    Test Engineer, Process Engineer, Materials Engineering, Electrical Engineering
Salary/Wage Range or Industry Benchmark: 120000 - 190000 USD Yearly USD 120000.00 190000.00 YEAR
Job Description & How to Apply Below
Position: MTS - HBM Thermal Integration Engineer Richardson, Texas, United States of America Posted a day ago
## MTS - HBM Thermal Integration Engineer Richardson, Texas, United States of America Apply Now Find out how well you match with this jobJob :
JR114768
** Our vision is to transform how the world uses information to enrich life for
* all*.
** Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever.

The Heterogeneous Integration Group (HIG) sits within the Technology and Products Group (TPG) and develops industry-leading High Bandwidth Memory (HBM) solutions for next-generation AI and high-performance computing systems.  Micron is seeking an experienced MTS - HBM Thermal Integration Engineer to drive thermal performance optimization for next-generation High Bandwidth Memory products. This role sits at the intersection of thermal simulation, silicon characterization, process technology, package development, manufacturing, test engineering, and product integration.
** Key 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) to accelerate technology understanding
* 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 understanding and correlation between predictive models and measured silicon performance.
* Work closely 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.
** Minimum Qualifications
*** PhD with 5+ years of industry experience, or Master’s degree with 10+ years of industry experience, in Mechanical Engineering, Materials Science, Physics, Semiconductor Engineering, Electrical Engineering, or a related technical field
* Hands-on experience in semiconductor product development within memory, logic, or advanced packaging technologies, with a background in one or more of the following areas:
Process Integration, Package Integration, Product Engineering, or Yield Engineering
* Working knowledge of thermal simulation methodologies and multiphysics modeling approaches, with 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, inline metrology data, characterization results manufacturing data, and test results to identify performance drivers and sources of variation.
* Leverages AI-enabled tools and workflows to analyze data, automate routine tasks, improve decision-making, and enhance the efficiency and quality of assigned responsibilities
** Preferred Qualifications
*** 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…
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