Machine Learning Engineer

About the Company

BeyondMath is a pioneering startup, backed by top-tier VCs, on a mission to reshape the frontiers of engineering through Foundational AI models for Physics. We are replacing traditional, slow and expensive simulation methods with AI that rivals accuracy at orders of magnitude higher speed.

Responsibilities

• Design and train deep learning models for physics simulation across aerodynamic and engineering domains
• Drive optimization efforts for model inference speed, accuracy, and robustness on large-scale industrial datasets
• Research effective ways to represent geometric design variations for efficient use by machine learning models
• Partner with engineering teams to deploy and monitor models in production-grade pipelines and tools
• Contribute to design decisions around model and data architecture, tooling, and ML infrastructure

Requirements

• Strong track record applying ML to complex real-world problems
• Deep understanding of machine learning theory, including optimization and generalization
• Strong Python skills
• Experience with deep learning libraries such as TensorFlow, PyTorch, or JAX
• Master's Degree or PhD in Machine Learning, Computer Science, or a related quantitative field
• Ability to explain complex ML concepts to technical and non-technical audiences

Preferred Qualifications

• Familiarity with aerodynamic principles and computational fluid dynamics (CFD)
• Prior experience in optimization algorithms for engineering design
• Experience integrating physical laws or constraints into machine learning models