Accelerated Physics Simulation Engineer – Agentic Computational Engineering (ACE)

Voyager Technologies is an innovative defense, national security, and space technology company committed to advancing transformative solutions. The Accelerated Physics Simulation Engineer will develop high-fidelity physics simulation capabilities to optimize hardware designs using AI agents, working with numerical methods, GPU computing, and machine learning. Responsibilities Design and implement fast physics solvers (e.g., CFD, thermal, structural, plasma) suitable for use inside agentic optimization loops Develop surrogate models (e.g., physics-informed neural networks, neural operators, graph neural networks) that approximate high-fidelity simulations at orders-of-magnitude lower cost Integrate accelerated solvers and surrogates into the ACE platform so AI agents can call them as tools during design and optimization Work with the ACE Applications Lead (Mechanical/Propulsion) to identify key regimes and quantities of interest and to ensure that accelerated models remain physically credible Create and curate training and validation datasets by coupling commercial or open-source solvers (e.g., Ansys, COMSOL, Star-CCM+, OpenFOAM) with automated parameter sweeps Profile and optimize GPU kernels and numerical pipelines, targeting large speedups over baseline codes while preserving required accuracy Develop test harnesses, benchmarks, and diagnostics that track accuracy, stability, and performance of accelerated models over time Use LLMs to accelerate boilerplate coding, experiment scripting, and documentation so you can focus on core numerical and physical insights Leverage the most advanced LLMs and tooling to assist with complex mathematics and numerical simulation generation Skills PhD in Computational Physics, Mechanical or Aerospace Engineering, Applied Mathematics, Computer Science (with a focus on numerical methods), or a related field; or Master's degree + 3 years of highly relevant experience 0–3 years of post-PhD industry, startup, or postdoctoral experience (or 3–6 years total experience working in computational science/engineering) Hands-on experience implementing numerical methods for PDEs (e.g., FEM, FVM, FDM, particle or mesh-free methods) in research or production environments Experience with at least one major scientific computing or ML framework (e.g., JAX, PyTorch, TensorFlow) and one GPU or performance-oriented technology (e.g., CUDA, PhysicsNEMO, etc) Demonstrated experience speeding up simulations or building surrogate models for physics problems, with quantitative before/after results Demonstrated 'AI-first' workflow: you use LLMs to help generate, refactor, and test code so you can spend more time on modeling and physics Experience with CFD, structural mechanics, heat transfer, or plasma physics as applied to aerospace or propulsion systems Experience with electrical, power, and electromagnetic simulations as applied to PCB or RF systems Prior work on physics-informed neural networks (PINNs), neural operators (FNO, UNO, etc.), or other ML-based surrogates for physical systems Experience coupling commercial or open-source solvers (e.g., Ansys, COMSOL, Star-CCM+, OpenFOAM) with custom automation or optimization code Familiarity with differentiable programming and adjoint methods for design optimization A track record of side projects, open-source contributions, or competition results that demonstrate deep enthusiasm for computational physics and performance engineering Benefits Competitive salary Discretionary annual bonus plan Paid time off (PTO) Comprehensive health benefit package Retirement savings Wellness program Various other benefits Company Overview Voyager Technologies is a defense and space technology company that develops solutions for national security and commercial space missions. It was founded in 2019, and is headquartered in Denver, Colorado, USA, with a workforce of 501-1000 employees. Its website is