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Stand · 1 day ago

Physics Simulation Engineer

San Francisco, CA

Full-time

Hybrid

Senior Level

$160K/yr - $210K/yr

5+ years exp

Stand is a new technology and insurance company focused on revolutionizing climate risk assessment and mitigation. As a Physics Simulation Engineer, you will develop and deploy advanced computational physics models, collaborating in a highly interdisciplinary environment to enhance risk modeling and mitigation strategies.

InsuranceInsurTechProperty Insurance

No H1B

Hiring Manager

Leah Metz

Responsibilities

Own our core CFD/thermofluid solvers and their supporting scripts and infrastructure

Translate real-world physics into simulation code (e.g., combustion, wind dynamics)

Tune and validate models and methods against empirical data and experiments

Run simulations and communicate results to cross-functional teams

Accelerate traditional numerical solvers and simulation runtimes

Support the development of AI-driven physics models alongside researchers and engineers

Qualification

CFDFortranC++ThermofluidsPythonParallel programmingHPC workflowsMeshingCommunicationSelf-motivatedAdaptable

Required

PhD or Master's in relevant field and 5+ years of experience with CFD, including simulation design, execution, and validation

Proficiency with Fortran-based solvers, including both running existing models and extending/augmenting their functionality; fluency in C++, Python, or similar for scripting, integration, and tooling

Strong intuition in thermofluids and heat transfer, including combustion modeling and radiation

Proven ability to communicate and integrate technical knowledge across teams

Experience calibrating and validating simulations against physical test results

Experience with parallel programming (OpenMP, MPI), HPC workflows, and GPU acceleration

Expertise in meshing, discretization, and pre-processing to align resolution with task complexity

Highly self-motivated, with a 'run-through walls to get the problem solved' method, self-directed, proactive, and adaptable; comfortable operating in fast-paced, ambiguous environments where problems, interfaces, and priorities evolve over time