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Boise, ID - ID1
Source: Micron careers · View original posting
From Micron's posting. “We” and “our” refer to the employer.
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.
At Micron-Boise, ID, we are undergoing a historic $15 billion investment in semiconductor manufacturing; construction began in early 2023, with DRAM production slated for the second half of the decade.
As a leader in the semiconductor industry, we build solutions that inspire and transform technology. With plans to invest more than $150 billion globally over the next decade in leading-edge manufacturing, we are looking for passionate people to join our Boise expansion team and contribute to the growth and innovation of the semiconductor industry.
As a Senior Wet Etch Process Engineer you will be primarily responsible for starting up, developing, and optimizing processes to improve product quality, driving process yield improvements, cost reduction, productivity improvement and risk management as well as resolving manufacturing line problems. Your expertise will give to the production of high-quality semiconductor components that are pivotal to our customers' success.
You will work closely with multi-functional teams to tackle process issues and implement solutions that improve efficiency and yield. Your passion for engineering and willingness to learn will help us overcome the challenges of this fast-paced industry. We are looking for someone who enjoys hands-on work, values collaboration, and is eager to dive deep into the technical aspects of semiconductor manufacturing.
You are also expected to leverage digital and AI-driven tools to enhance process monitoring, data analysis, and decision-making. This includes applying AI/LLM/automation solutions for defect analysis, yield optimization, trend detection, and reporting efficiency, as well as utilizing data-driven insights to improve process control and manufacturing performance.
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