Godela (YC X25)
Overview Direct message the job poster from Godela (YC X25)
Find out more about the daily tasks, overall responsibilities, and required experience for this opportunity by scrolling down now. At Godela, we're building the first Physics Foundation Model; a physics-informed AI platform learns from simulation, experiment, and equations to instantly predict and simulate physical behavior. We’re scaling deep-learning surrogates so every engineer has the power of an R&D lab at their fingertips to turn months of simulation and experimentation into minutes. Founding Simulation Engineer We are seeking a Founding Simulation & Data Engineer to help us build and scale the world\'s first Physics Foundation Model. This role is a strategic pillar, focusing on defining the data engine and validation strategy required to ensure our models accurately capture the complex physical world. Responsibilities
Define the methodology for representing physical systems in data and models—balancing accuracy, scale, and generalization. Own the strategy for validating and verifying our model outputs against ground-truth simulation and experimental data. Generate and curate simulation data across multiple physics domains (CFD, FEA, multiphysics), ensuring high-fidelity coverage of complex behaviors. Build scalable pipelines and standards for turning simulation and experimental data into training-ready datasets. Drive the research and engineering of novel techniques for data augmentation, curation, and generation Qualifications
Hands-on CAD generation and Simulation Expertise: Deep experience with one or more simulation domains (e.g., CFD, FEM, DEM) and commercial or open-source solvers (e.g., Star-CCM+, Fenics/dolfinx, OpenFOAM). Robust Programming Skills: Strong proficiency in Python is a must. Experience with C++ or other compiled languages for performance-critical tasks is a big plus. Data Pipelining Experience: Proven track record of building and managing data pipelines for large datasets, preferably in a scientific or engineering context. Problem-Solving Mentality: A demonstrated ability to creatively solve complex, unstructured problems. Nice-to-haves
Familiarity with ML frameworks like PyTorch, JAX, or TensorFlow. Experience with parallel and distributed computing for simulation or data processing. Experience with Graph Neural Networks, Physics-Informed Neural Networks, Neural Operators, and Transformer architectures Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries: Research Services
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Find out more about the daily tasks, overall responsibilities, and required experience for this opportunity by scrolling down now. At Godela, we're building the first Physics Foundation Model; a physics-informed AI platform learns from simulation, experiment, and equations to instantly predict and simulate physical behavior. We’re scaling deep-learning surrogates so every engineer has the power of an R&D lab at their fingertips to turn months of simulation and experimentation into minutes. Founding Simulation Engineer We are seeking a Founding Simulation & Data Engineer to help us build and scale the world\'s first Physics Foundation Model. This role is a strategic pillar, focusing on defining the data engine and validation strategy required to ensure our models accurately capture the complex physical world. Responsibilities
Define the methodology for representing physical systems in data and models—balancing accuracy, scale, and generalization. Own the strategy for validating and verifying our model outputs against ground-truth simulation and experimental data. Generate and curate simulation data across multiple physics domains (CFD, FEA, multiphysics), ensuring high-fidelity coverage of complex behaviors. Build scalable pipelines and standards for turning simulation and experimental data into training-ready datasets. Drive the research and engineering of novel techniques for data augmentation, curation, and generation Qualifications
Hands-on CAD generation and Simulation Expertise: Deep experience with one or more simulation domains (e.g., CFD, FEM, DEM) and commercial or open-source solvers (e.g., Star-CCM+, Fenics/dolfinx, OpenFOAM). Robust Programming Skills: Strong proficiency in Python is a must. Experience with C++ or other compiled languages for performance-critical tasks is a big plus. Data Pipelining Experience: Proven track record of building and managing data pipelines for large datasets, preferably in a scientific or engineering context. Problem-Solving Mentality: A demonstrated ability to creatively solve complex, unstructured problems. Nice-to-haves
Familiarity with ML frameworks like PyTorch, JAX, or TensorFlow. Experience with parallel and distributed computing for simulation or data processing. Experience with Graph Neural Networks, Physics-Informed Neural Networks, Neural Operators, and Transformer architectures Seniority level
Mid-Senior level Employment type
Full-time Job function
Engineering and Information Technology Industries: Research Services
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