Match Score
Against your primary resumeLogin to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Protocol Intelligence
Data-driven signals on your job's competitivenessLog in to see why each signal reads the way it does.
Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and improve GenAI-powered systems supporting ASIC semiconductor engineering workflows including code generation, analytics, documentation automation, and failure analysis.
Develop, optimize, and operationalize LLM-based AI/ML solutions and workflows such as retrieval-augmented generation (RAG) and agentic workflows in cloud and enterprise environments.
Collaborate cross-functionally to translate complex engineering challenges into scalable AI/ML systems, and communicate findings effectively to technical and non-technical stakeholders.
Minimum Requirements
Bachelor's degree with 10+ years or Master’s degree with 8+ years in Electrical Engineering, Computer Science, Data Science, Statistics, Artificial Intelligence, or related field.
At least 4 years of hands-on experience developing and deploying AI applications in semiconductors, electronics, or related engineering industries.
Strong programming skills in Python and practical experience with AI coding tools (e.g., Claude Code, Cursor, Gemini CLI) and LLM-based systems including RAG and agentic workflows.
Work Experience Required: Minimum 4 years in relevant AI application deployment; Notice Period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experience building AI/ML solutions specifically for ASIC semiconductor pre-silicon and post-silicon workflows.
Well-versed in deploying ML pipelines in cloud platforms such as GCP, AWS, or Azure with focus on production readiness and scalability.
Capable of working across multi-functional teams combining systems architecture, engineering, data science, and IT to deliver enterprise-grade AI/ML products.