Director of AI/ML Engineering (EDA & Semiconductor Design)
Core
Lead the definition and execution of AI/ML-driven initiatives to drive adoption across frontend and backend design flows, enabling next-generation intelligent design automation for semiconductor engineering.
Role type
Director of AI/ML Engineering (EDA & Semiconductor Design)
Builds
AI-driven (agentic) solutions for Frontend (modelling, synthesis, optimization) and Backend (place-and-route, timing closure, physical optimization) semiconductor design workflows.
Domain
Semiconductor industry, Electronic Design Automation (EDA), AI/ML engineering
Deliverable
production ML models | product features
Required skills
AI/ML strategy definition, agentic solution deployment, end-to-end AI integration into toolchains, scalable data pipeline management, model training/fine-tuning/validation/deployment, cross-functional leadership, KPI definition for productivity/ROI, enterprise AI governance alignment, emerging AI/ML technology adoption
Preferred skills
EDA tools and chip design flows expertise, AI/ML frameworks (TensorFlow, PyTorch), AI-driven design optimization solutions, cloud platforms and scalable compute infrastructure
Technologies
LangChain, vector databases, RAG-based architectures, LLM ecosystems, embeddings, knowledge retrieval, TensorFlow, PyTorch
Responsibilities
Define and own AI/ML strategy for Engineering group's software and design flows; Lead transformation of semiconductor design workflows by deploying AI-driven solutions; Establish scalable frameworks for data collection, labelling, and pipeline management; Lead cross-functional collaboration with EDA, design, architecture, and platform teams; Build and grow a high-performance engineering team; Define KPIs to measure productivity gains, quality improvements, and ROI; Ensure alignment with enterprise AI programs and governance frameworks; Drive continuous innovation and adoption of emerging AI/ML technologies.
Seniority
Director, strategic leadership with hands-on technical oversight
