Physics Simulation Engineer

Stand Insurance•San Francisco, CA

2d•$160,000 - $210,000•Onsite

About The Position

As a Physics Simulation Engineer on the Applied Science team, you’ll play a key role in developing and deploying advanced computational physics models, collaborating closely with engineers, technologists, and leadership in a highly interdisciplinary environment. We’re investing in physics-based simulation as a core capability to model and mitigate risk. This includes adapting traditionally high-cost engineering methods (e.g., CFD, FEA) into scalable, automated tools that operate orders of magnitude faster. You’ll also help us train machine learning models to understand the underlying laws of deterministic physics—transforming legacy workflows into modern, accessible systems. This role offers a front-row seat to shaping how high-fidelity simulation and AI intersect to characterize the physical world.

Requirements

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.

Nice To Haves

Production experience with CFD and FEA, including hands-on development of multiphysics and/or fluid–structure interaction (FSI) models.
Direct experience modifying (not just running) Fortran- or C++-based solvers.
Demonstrated history of accelerating solvers on HPC clusters, GPUs, or distributed systems, with measurable runtime or throughput gains.
Experience validating simulations against experimental or field data, including quantified error analysis and benchmarking.
Experience integrating or developing hybrid physics/ML models, including reduced-order or surrogate modeling approaches.

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.