IC Design AI/ML Silicon Debug & Yield Engineer

Responsibilities

• AI-Driven Debug: Develop and deploy ML models to automate the classification of scan failures (Chain, Stuck-at, Transition) and correlate them with design-for-test (DFT) structures.
• Predictive Yield Modeling: Integrate high-dimensional data-including Fab process parameters, PCM (Process Control Monitoring), and E-test data-to predict yield excursions before they hit the assembly line.
• Holistic Yield Analysis: Look beyond the bitcell. You'll analyze the interplay between design marginalities, voltage scaling, and manufacturing variations.
• Tool Orchestration: Evaluate and implement cutting-edge AI-based EDA tools for root-cause analysis and systematic defect identification.
• Cross-Functional Leadership: Act as the "translator" between the Fab, Design, and Test teams, using data to prove where the silicon is diverging from the simulation.
• The Ideal Candidate
• ASIC Design Engineering: Deep understanding of ASIC design, including logic circuits, memory, PLL/Analog, Place and route, STA, DFT, DFM, etc.
• The Debug Specialist: You know your way around scan compression, BIST, and ATPG patterns. You understand what a "shmoo plot" is telling you about a timing marginality.
• The Data Scientist: You don't just "use" tools; you understand the math. You are proficient in Python (Pandas, Scikit-Learn, PyTorch/TensorFlow) for building custom analysis pipelines.
• The Yield Strategist: You have a deep understanding of semiconductor manufacturing processes (FinFET nodes) and how physical defects manifest as logical failures.
• Technical Requirements
• Bachelor's degree plus 8+ years of related experience OR Master's degree plus 6+ years of related experience
• 3+ years in Silicon Debug, DFT, or Yield Engineering.
• Knowledge of Deep Sub-micron (FinFET) effects, including IR drop, crosstalk, and process variation
• Experience with Pattern Recognition, Clustering (for defect binning), and Regression models.
• Expertise in Python, SQL, and big data environments (Spark, Snowflake, etc.).
• Familiarity with industry-standard yield management systems (e.g., PDF Solutions, Synopsys YieldExplorer, or Cadence Clarity).
• Additional Job Description:
• Compensation and Benefits
• The annual base salary range for this position is $ 108,000 - $192,000
• This position is also eligible for a discretionary annual bonus in accordance with relevant plan documents, and equity in accordance with equity plan documents and equity award agreements.
• If you are located outside USA, please be sure to fill out a home address as this will be used for future correspondence.

Benefits

Additional Information

Please Note: 1. If you are a first time user, please create your candidate login account before you apply for a job. (Click Sign In > Create Account) 2. If you already have a Candidate Account, please Sign-In before you apply. Job Description: We need an engineer to own the end-to-end silicon diagnostic pipeline. You won't just be looking at reports; you will be building the engines that generate them. In this role, you will ingest massive volumes of scan failure data and process parameters, using AI-driven methodologies to find the "needle in the haystack" that is hindering our yield. Your goal is simple but ambitious: Use AI/ML to transform millions of data points into actionable insights that drive aggressive yield ramps and shorten time-to-market.

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