Ph.D. Intern - AI/ML & Design Automation
Core
Deploying machine learning and AI systems to accelerate semiconductor chip design and verification, or building internal enterprise AI tools for engineering workflows.
Role type
Ph.D. Research Intern (AI/ML)
Builds
Production ML models for EDA automation, predictive silicon design, and internal agentic AI platforms
Domain
Semiconductor / Hardware Design Automation / Enterprise AI Infrastructure
Deliverable
production ML models | product features
Required skills
Machine learning model training and deployment, Python programming, experimental design and data analysis, graph neural networks, reinforcement learning, large language model integration, agentic workflow design, RAG pipelines
Preferred skills
VLSI design knowledge, EDA tool familiarity (Cadence/Synopsys), multi-agent orchestration frameworks (LangChain, AutoGen), diffusion models
Technologies
PyTorch, TensorFlow, Python, Git, Claude, LangChain, LangGraph, AutoGen, CrewAI, LlamaIndex, Hugging Face, MCP, A2A
Responsibilities
Develop ML models for chip placement, routing, and timing closure; Build predictive models to reduce design iteration cycles; Design and implement LLM-based tools and agentic workflows for engineering teams; Evaluate model performance and safety in production environments; Collaborate with design engineers and IT stakeholders to validate and deploy AI solutions
Seniority
Ph.D. Candidate, Research Intern
