Back
Tier-1 brand but semiconductor specialization limits applicant pool, yielding moderate competition.
Requires semiconductor domain knowledge plus ML skills, making cross-industry fit moderately constrained.
Multiple mandatory technical skills (ML, Python, pipelines) but no strict years specified, so medium strictness.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop and deploy AI/ML models for design validation, process optimization, and simulation acceleration.
Automate workflows in design, routing, simulation, and validation while creating data pipelines integrating design, simulation, and manufacturing data.
Collaborate across design, simulation, and manufacturing teams to build engineering-focused AI tools and translate engineering problems into scalable AI and automation solutions.
Hands-on experience with Machine Learning and Data Analytics.
Proficiency in Python and engineering automation scripting.
Understanding of IC packaging, layout, routing, and simulation preferred (not strictly mandatory).
Bachelor’s or Master’s degree in Mechanical, Electrical, Electronics, or Semiconductor Engineering.
Experience in semiconductor packaging or ASIC/DRAM/NAND domains, indicating domain familiarity with memory and storage technologies.
Proven ability to build engineering-focused AI tools or platforms and work on data pipelines and predictive models.
Comfortable translating complex engineering problems into scalable AI and automation solutions across multidisciplinary teams.