Technical Lead – AI Systems & Architecture
Core
Applying state-of-the-art AI and ML technologies to solve complex business problems in chip design, qualification, and debug engineering processes through intelligent automation and data-driven insights.
Role type
Senior IC machine-learning engineer (semiconductor engineering)
Builds
Scalable data pipelines, custom ML models, and engineering tools for chip design and debug
Domain
Semiconductor / Hardware Engineering / AI & Machine Learning
Deliverable
production ML models
Required skills
Python, C++, supervised and unsupervised learning, deep neural networks (RNNs, Transformers), ML frameworks (scikit-learn, TensorFlow, PyTorch), GenAI/LLMs/RAG, statistical analysis, feature engineering, GPU/CUDA/High Performance Computing
Preferred skills
PhD in CS/Data Science, large model development from scratch, time series analysis (ANOVA, ARIMA), SQL/ETL/Cloud (AWS), distributed computing, LangChain, software design & architecture
Technologies
Python, C++, TensorFlow, PyTorch, scikit-learn, Pandas, NumPy, Matplotlib, CUDA, AWS, LangChain, RAG
Responsibilities
Design and implement end-to-end data analytics workflows for semiconductor use cases; Develop, train, and optimize ML models using supervised, unsupervised, and deep learning techniques; Build scalable data ingestion and transformation pipelines; Apply statistical analysis and visualization techniques to derive insights; Experiment with GenAI platforms, LLMs, and RAG techniques; Collaborate with cross-functional teams to integrate ML models into engineering workflows
Seniority
Senior, hands-on IC
