Senior AI Engineer , Physics AI
Core
Build physics-AI capability by turning engineering inputs into qualified surrogate models and production software for AI Factory design, optimization, simulation, and operations.
Role type
Senior IC scientific machine learning engineer (physics-informed)
Builds
Surrogate models, training pipelines, model registry, inference APIs, and scenario-orchestration integrations for thermal, airflow, cooling, and infrastructure systems
Domain
AI infrastructure, energy systems, computational engineering, liquid cooling
Deliverable
production ML models
Required skills
scientific machine learning, surrogate modeling, neural operators, graph neural networks, reduced-order modeling, physics-informed learning, Python, PyTorch, GPU infrastructure deployment, Ansys Fluent integration, model qualification, uncertainty quantification
Preferred skills
cross-disciplinary program leadership, experience taking models from research to production, familiarity with Omniverse and OpenUSD
Technologies
PyTorch, Python, Ansys Fluent, Omniverse, OpenUSD, GPU infrastructure
Responsibilities
Develop and qualify surrogate models for bounded thermal and cooling scenarios; Build reproducible pipelines from engineering tools to model-ready datasets; Deliver tested, versioned software with inference APIs and monitoring; Implement applicability-domain checks and uncertainty quantification; Integrate surrogates into whole-factory decision support and design comparisons
