VLSI Engineer

Responsibilities:Design, develop, troubleshoot, or debug software tools for the development of integrated circuitsSupport a global design teamInterface with foundries, configure the IP Project environment and design flows for IOLIBS & ESD.Develop routines and utility programs to automate the design environmentBuild productive internal/external working relationshipsRequirementsDegree in electronic/micro electronic engineering or computer science4+ years of relevant experienceGood knowledge of hardware integrated circuits and UNIX/Linux user knowledgeProficiency with at least one programming language and scripting languages to automate processesGood English communication skillsGood analysis and problem-solving skills and the ability to exercise good judgmentExperience in Python, TCL or Shell scriptingExperience with VLSI domain like familiarity with DRC/LVS Extraction/Simulation/EMIRCadence, Custom Compiler EDA tool usageIC design experienceExperience in data management and job schedule tool like LSF/GRID EngineBenefitsAzure 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.