Micron
CVD Equipment Development Engineer, Advanced Memory Pathfinding
$159K–$271K
Albany, NY · Full-time · Posted Oct 29, 2026
- Experience
- Five or more years; semiconductor equipment engineering, equipment development, technology development, or related experience.
- Education
- Bachelor’s degree in Mechanical Engineering, Electrical Engineering, Mechatronics, Chemical Engineering, Materials Science, Physics, or a related technical field.
About the job
Develop and qualify advanced CVD and thin-film equipment for High-NA EUV and next-generation DRAM pathfinding, working with suppliers and cross-functional teams to mature equipment and prepare capabilities for transfer.
What you'll do
- Develop equipment specifications, hardware configurations, controls, and qualification plans based on technology needs; support installation, startup, and qualification.
- Partner with suppliers and internal teams to mature equipment, influence supplier roadmaps, and investigate equipment performance issues.
- Use equipment data, sensors, statistical methods, modeling, and AI-assisted analytics to assess capability and accelerate root-cause analysis; document transfer requirements.
What they ask for
- Bachelor’s degree in a listed or related technical field.
- Five or more years of semiconductor equipment engineering, equipment development, technology development, or related experience.
- Experience developing, installing, qualifying, improving, or troubleshooting complex semiconductor equipment.
- Experience using AI tools for productivity.
Nice to have
- Master’s degree or Ph.D. in an applicable engineering or scientific field or equivalent experience.
- Experience with first-of-a-kind or advanced semiconductor equipment, or with DRAM, CVD, PECVD, ALD, thermal deposition, precursor delivery, thin-film metrology, or related equipment systems.
Pay
$159,000.00 - $271,000.00 a year (USD; base salary)
Tools
CVD, PECVD, ALD, High-NA EUV, DRAM
AI focus
Use AI-assisted analytics with equipment signals, fault-detection data, sensors, and process results to identify anomalies, accelerate root-cause analysis, and improve decision quality; experience using AI tools for productivity is required.
Model-written summary · the original posting is authoritative