You will apply your expertise in GenAI agentic frameworks and physical synthesis to develop intelligent automation solutions that transform our RTL-to-GDS implementation flows. You will be directly responsible for creating AI-powered agents using technologies like Model Context Protocol (MCP) that can autonomously optimize physical synthesis processes predict design challenges and recommend solutions.
- Experience with GenAI frameworks large language models and AI agent development
- Experience with industry standard Synthesis tools such as Fusion Compiler or Genus
- Scripting skills in TCL Python or Perl for EDA tool automation
- Minimum requirement of BS 3 years of relevant industry experience
- Understanding of physical synthesis concepts and CAD flows
- Experience in Python AI/ML libraries (PyTorch TensorFlow Transformers) and MCP or similar agentic frameworks
- Experience developing AI agents or autonomous systems for technical domains
- Knowledge of prompt engineering RAG (Retrieval-Augmented Generation) and fine-tuning techniques
- Experience with agentic AI frameworks beyond MCP (AutoGen CrewAI LangChain agents etc.)
- Background in CAD flow or frontend methodology development combined with AI/ML expertise
- Experience with Low Power implementation flows (UPF) and AI-driven power optimization
- Familiarity with logical equivalence tools (Conformal LEC Formality) and opportunities for AI enhancement
- Knowledge of static timing analysis place and route tools and potential AI applications in these domains
- Experience with cloud platforms and distributed AI model deployment
- Publications or demonstrated expertise in AI applications for EDA or chip design
You will apply your expertise in GenAI agentic frameworks and physical synthesis to develop intelligent automation solutions that transform our RTL-to-GDS implementation flows. You will be directly responsible for creating AI-powered agents using technologies like Model Context Protocol (MCP) that c...
You will apply your expertise in GenAI agentic frameworks and physical synthesis to develop intelligent automation solutions that transform our RTL-to-GDS implementation flows. You will be directly responsible for creating AI-powered agents using technologies like Model Context Protocol (MCP) that can autonomously optimize physical synthesis processes predict design challenges and recommend solutions.
- Experience with GenAI frameworks large language models and AI agent development
- Experience with industry standard Synthesis tools such as Fusion Compiler or Genus
- Scripting skills in TCL Python or Perl for EDA tool automation
- Minimum requirement of BS 3 years of relevant industry experience
- Understanding of physical synthesis concepts and CAD flows
- Experience in Python AI/ML libraries (PyTorch TensorFlow Transformers) and MCP or similar agentic frameworks
- Experience developing AI agents or autonomous systems for technical domains
- Knowledge of prompt engineering RAG (Retrieval-Augmented Generation) and fine-tuning techniques
- Experience with agentic AI frameworks beyond MCP (AutoGen CrewAI LangChain agents etc.)
- Background in CAD flow or frontend methodology development combined with AI/ML expertise
- Experience with Low Power implementation flows (UPF) and AI-driven power optimization
- Familiarity with logical equivalence tools (Conformal LEC Formality) and opportunities for AI enhancement
- Knowledge of static timing analysis place and route tools and potential AI applications in these domains
- Experience with cloud platforms and distributed AI model deployment
- Publications or demonstrated expertise in AI applications for EDA or chip design
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