VLSI Engineer

Dew Software, a leading digital transformation company, is seeking a highly skilled VLSI Engineer to join our team. As a VLSI Engineer at Dew Software, you will have the opportunity to work on cutting-edge semiconductor projects and contribute to the design and development of advanced integrated circuits. We are committed to pushing the boundaries of technology and delivering innovative solutions to our clients. Join our team and be part of a dynamic and collaborative work environment that fosters creativity, growth, and career development.

Responsibilities:
• Design, develop, troubleshoot, or debug software tools for the development of integrated circuits
• Support a global design team
• Interface with foundries, configure the IP Project environment and design flows for IOLIBS & ESD
• Develop routines and utility programs to automate the design environment
• Build productive internal/external working relationships

Requirements
• Degree in electronic/micro electronic engineering or computer science
• 4+ years of relevant experience
• Good knowledge of hardware integrated circuits and UNIX/Linux user knowledge
• Proficiency with at least one programming language and scripting languages to automate processes
• Good English communication skills
• Good analysis and problem-solving skills and the ability to exercise good judgment
• Experience in Python, TCL or Shell scripting
• Experience with VLSI domain like familiarity with DRC/LVS Extraction/Simulation/EMIR
• Cadence, Custom Compiler EDA tool usage
• IC design experience
• Experience in data management and job schedule tool like LSF/GRID Engine

Benefits
• Azure 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