Physics Informed Machine Learning Scientist
Core
Building integrated master-model frameworks to capture multi-physics behavior of laser-produced plasma lithography light source systems, enabling system-level optimization and reducing uncertainty in future source configurations.
Role type
Senior IC physics-informed machine learning scientist (lithography)
Builds
Integrated master-model frameworks for virtual source technology
Domain
Semiconductor lithography / Laser-produced plasma (LPP) / Multi-physics modeling
Deliverable
production ML models
Required skills
Physics-informed machine learning, optimization, deep learning, data pipeline development, model integration, experimental design, code troubleshooting
Preferred skills
C/C++, Matlab, cloud environments (AKS, GDCE, Spark, Databricks), database tools, automation frameworks, experimental tracking platforms (MLflow)
Technologies
PyTorch, JAX, Python, Azure Kubernetes Service, Google Distributed Cloud Edge, Apache Spark, Azure Databricks, MLflow
Responsibilities
Establish scalable data management frameworks for legacy and new datasets; Develop physics-informed ML models and scientific simulations for system-level tradeoff analysis; Adapt and integrate existing physics-based models into a master virtual model; Propose experimental anchoring studies and analyze test results to reduce model uncertainty; Provide input to technology roadmaps and contribute to experimental design; Troubleshoot code and algorithms for source operation and data streaming; Document learnings and communicate knowledge to engineering and product teams
Seniority
Senior, hands-on IC