Principal Data Scientist, Agentic Platform
Build AI systems that optimize semiconductor design, engineering, validation, and manufacturing workflows using large-scale data Architect agentic AI systems that integrate with modeling tools, EDA platforms, design environments, and product/test ecosystems Define and promote Best Known Methods for deploying LLMs and agentic systems in production environments Evaluate and refine models using structured benchmarking, tuning, RLHF, and continuous feedback Work with process, design, product, and test engineering teams to identify high-impact opportunities and deliver scalable solutions Master's, PhD, or equivalent experience in Electrical Engineering, Computer Science, or related field with 10+ years relevant experience Proficient in Python with experience working with semiconductor design and process datasets Experience using enterprise data platforms such as Snowflake, BigQuery, MSSQL, Oracle, or Redshift Hands-on experience developing and deploying AI/ML systems involving LLMs, RAG, agentic workflows, and frameworks such as PyTorch or TensorFlow Experience training and optimizing domain-adapted LLMs, including pretraining, post-training on synthetic datasets, and model quantization Cloud experience with GCP, AWS, or Azure, including deploying ML pipelines in production Demonstrated ability to lead AI/ML initiatives independently in semiconductor or hardware environments Experience applying AI/ML directly to semiconductor design, fabrication, or validation Deep understanding of semiconductor-specific AI/ML applications Experience with CI/CD and MLOps for ML/LLM deployment Familiarity with agentic AI frameworks such as LangGraph or AutoGen and evaluation tools like AgentEval Strong ability to translate complex technical concepts into practical solutions for cross-functional teams
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