PV/STA Engineer
2 weeks ago
Responsibilities
Perform post-verification testing to validate the functionality and performance of semiconductor productsAnalyze test data and generate detailed reports outlining measurement results and findingsCollaborate with design and test teams to identify and troubleshoot issuesDevelop methodologies and tools for data analysis and interpretationDesign and implement test programs and test flowsConduct statistical analysis and provide insights for improvementsStay up-to-date with industry trends and advancements in semiconductor testing and analysisRequirementsConstraint development – work with RTL team on clock constraint and timing exception. Reading through 3 party IP datasheet and work on timing constraint.Partition budgeting – push down from FC level STA and fine tune.Timing Model build and checklist for all the mode/corner.FC timing convergence include intra and inter partition. Work with PEO on physical optimization.Timing ECO including automated flow (tweaker/prime closure) and manual eco tcl, timing eco for checklistBenefitsAzure Infrastructure Experience:
Proficiency in managing Azure infrastructure components, including virtual machines, storage, and networking, to support AI model development and deployment.CI/CD Pipeline Experience:
Experience with Continuous Integration/Continuous Deployment (CI/CD) pipelines, including the automation of model deployment processes.Containerization in the Cloud:
Strong knowledge of containerization technologies in the cloud, such as Docker and Kubernetes, for efficient deployment and scaling of machine learning models.Machine Learning Expertise:
Proficient in building and optimizing machine learning models, with a deep understanding of various ML algorithms and frameworks.Programming Skills:
Proficiency in programming languages commonly used in machine learning, such as Python and libraries like TensorFlow and PyTorch.Data Management:
Experience in data preprocessing, feature engineering, and data pipeline development for machine learning.Collaborative Team Player:
Excellent communication skills and the ability to work collaboratively with cross-functional teams, including AI engineers and SREs.Documentation:
Effective documentation skills to maintain clear and organized records of models, infrastructure configurations, and incident responses.
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