AI / ML Research Engineer

Role Description & Responsibilities

Join us in shaping the future of data-driven machine learning for accelerated numerical simulations. Our R&D Multiphysics Science & Technology group is seeking a highly motivated AI / Machine Learning Researcher eager to transform traditional physics-based simulations with cutting-edge neural network algorithms.

In this full-time role, you will focus on developing and refining neural network algorithms trained on historical data derived from physics-based numerical simulations (e.g., finite elements or finite volumes). Your work will be instrumental in advancing geometric and physics deep learning R&D to create 3D surrogate models for industrial and life science applications.

Key Responsibilities:

• Research and develop innovative non-parametric machine learning methods for accelerating physics-based simulations.
• Design, train, validate, and optimize neural networks using state-of-the-art ML frameworks (e.g., PyTorch, TensorFlow, JAX).
• Evaluate the predictive trustworthiness and computational efficiency of ML models compared to traditional physics-based simulations.
• Tackle high-impact real-world challenges in design, manufacturing and life sciences.
• Collaborate with global industry leaders, research institutions, and multidisciplinary teams.
• Stay ahead of emerging trends in geometric deep learning, physics-informed AI, and computational methods.
• Help develop data pipelines for data curation from diverse sources, both client-provided and internal.
• Contribute to software development activities for proof of concept towards productization in Python or C++.
• Document and maintain models, experiments, practices and findings for software production and/or publications (conferences/journals).