beyondmath - AI Researcher
Requirements
• PhD or MSc in Computer Science, Physics, Mathematics, or a related quantitative field. • 5+ years of post-grad experience in AI/ML research, with a demonstrable track record of models made it from the lab into production environments. • Deep Technical Mastery: Expert-level proficiency in PyTorch, JAX, or TensorFlow, with a focus on building custom layers, loss functions, and optimization loops. • Published Excellence: A strong record of high-quality publications in top-tier venues (e.g., NeurIPS, ICML, CVPR, or physics-specific AI journals). • Systems Thinking: Experience with scalable training infrastructure, including distributed training across GPU clusters and data pipeline automation. • Highly Desirable: • Physics-ML Expertise: Experience with Physics-Informed Neural Networks (PINNs), Operator Learning (DeepONet/FNO), or Equivariant Neural Networks. • Domain Knowledge: Familiarity with Aerodynamics, Fluid Dynamics, or Structural Mechanics. • Engineering Rigor: Familiarity with C++, CUDA for low-level model optimization.
Responsibilities
• Architect Physics-AI Foundations: Lead the research and development of novel ML architectures (e.g., Transformers, GNNs, or Diffusion models) designed specifically to solve complex partial differential equations (PDEs) including aerodynamic simulations. • Bridge Research & Production: Translate high-level mathematical concepts into clean, high-performance code. You won’t just "throw models over the wall"; you will ensure they are optimized for inference and integrated into our production design platform. • Advance Geometry Representation: Pioneer new ways to represent complex geometric design variations for efficient use in deep learning models. • Strategic Leadership: Mentor junior researchers and engineers. Help define our internal research standards, reproducibility pipelines, and high-performance compute (HPC) infrastructure requirements. • External Impact: Represent BeyondMath in the global AI community. Publish influential research at top-tier conferences (NeurIPS, ICML, ICLR) and position the company as the leader in "AI for Physics." • Cross-Functional Collaboration: Partner with CFD specialists and software engineers to ensure our models respect physical constraints while maintaining thespeed advantages of neural networks.
Benefits
• Full Ownership: You will have a direct seat at the table in shaping the future of a company redefining an entire industry. • High Impact: Your work will directly accelerate the transition to sustainable energy and more efficient transport. • Elite Team: Work alongside veterans from world-leading AI labs and engineering firms in a culture of "impact with integrity."
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