AI Research Scientist

About UsAxiomatic AI is building a new class of AI systems designed to reason with the rigor of the scientific method. By combining deep learning with formal logic and physics-based modeling, we create verifiable, interpretable AI systems that collaborate with and support human researchers in high-stakes scientific and engineering workflows.Our mission, 30×30Deliver a 30× improvement in the speed, accessibility, and cost of semiconductor and photonic hardware development by 2030. We aim to revolutionize hardware design and simulation in these industries and are building a team of highly motivated professionals to bring these innovations from research into commercial products.Position OverviewAs an AI Research Scientist specialized in computational science, you will lead the development of next-generation agentic‑AI‑aware computational science tools for physics simulations and engineering analysis and optimization. Your responsibilities will include designing, prototyping/evaluating, and deploying advanced scientific computing systems that integrate AI reasoning with traditional numerical methods. You will architect solutions for electromagnetic simulations and other computational physics tools while ensuring they maintain scientific rigor and verifiable accuracy. Close collaboration with our cross‑functional team, consisting of Mathematicians, Physicists, AI Engineers, and Software Engineers will be essential to deliver tools that transform how engineers and scientists approach computational problems.Your MissionAI-Driven Scientific Computing: Lead the development of tools and AI systems for the automation of scientific computing workflows, focused on electromagnetic simulations (FDTD, FEM) and associated inference, uncertainty quantification, and optimization tasks.Research & Innovation: Drive cutting‑edge research at the intersection of AI and computational science. Implement agent‑aware tooling for common computational science workflows alongside systems for verification of numerical accuracy and scientific rigor.Technical Leadership: Mentor junior scientists and engineers, establish best practices for scientific computing tool development, and guide architectural decisions that balance performance, accuracy, and usability.Collaboration & Integration: Work closely with domain experts in photonics and other fields to understand requirements and deliver tools that address real engineering challenges.Documentation & Outreach: Produce detailed technical documentation, publish research findings in top scientific computing and AI venues, and present results to both technical and business stakeholders.Key RequirementsPhD (or 3+ years of relevant industry experience) in Mathematics, Computer Science, Engineering, Physics, or a related field with focus on computational engineering/physics/statistics, control/optimization theory and practice, scientific computing, or numerical analysis.Background in PDE solving (or Bayesian) methods for inverse problems & uncertainty quantification with solid baseline understanding of numerical simulation & optimization methods, computational statistics, and scientific computing principles.Strong track record in developing numerical methods, frameworks for computational science, or tools for scientific computing.Expert-level proficiency in Python and/or other relevant scientific computing ecosystems (JAX, Julia, MPI, ...).Strong communication skills with ability to explain technical concepts to diverse audiences.Self‑motivated with a proactive, solution‑oriented mindset and ability to lead technical initiatives.Nice To HaveElectromagnetic Simulations: Hands‑on experience with FDTD, FEM, or other methods for solving Maxwell's equations; bonus for experience working with dedicated tools like MEEP, FEMWELL, Tidy3D, Lumerical, COMSOL, or other.PDE Simulations: Experience with CFD, structural mechanics, heat