Simulation Engineer
Simulation Engineers at AI companies build and operate the simulation infrastructure that supports training, validation, and design across two broadly distinct domains. The first is robotics and autonomous-systems simulation—physics solvers, sensor simulators, and high-fidelity virtual environments for training and validating robots, autonomous vehicles, and other embodied systems. The second is scientific and engineering simulation—finite-element analysis, computational fluid dynamics, atomistic and molecular simulation—used by AI-for-science and TechBio companies to validate predictions and generate training data. The two paths share methodological backbone (numerical methods, validation against experiment, automation at scale) but draw on different deep technical foundations. These engineers typically sit within dedicated simulation, research, or platform teams, collaborating with ML researchers, domain scientists, or robotics integrators depending on the application.
Skills
What companies are looking for in this role.
Building and maintaining high-fidelity simulation environments that accurately model real-world physics and behavior
Architecting scalable simulation frameworks and infrastructure for testing and training autonomous systems
Developing and validating computational models across multiple physics domains including thermal, mechanical, fluid, and electromagnetic systems
Designing and executing experiments to validate system performance and push simulation fidelity boundaries
Automating simulation tools and creating scalable optimization workflows for complex engineering problems
Debugging complex simulation systems and diagnosing discrepancies between simulation and physical reality
Performing domain analysis and identifying gaps between simulated and real-world behavior for improved model accuracy
Implementing and optimizing parametric CAD modeling and geometry workflows for simulation setup
Applying statistical and uncertainty quantification methods to simulation results and analysis
Training and evaluating machine learning models including large foundation models for simulation enhancement
Designing and implementing metrics to measure simulation fidelity and realism against real-world data
Integrating machine learning and generative AI models into simulation environments to improve realism and steerability
Developing reduced-order models and surrogate models to accelerate simulation while maintaining accuracy
Implementing policy learning and reinforcement learning approaches including imitation learning and offline RL
Performing system identification and contact modeling to enable sim-to-real transfer of learned behaviors
Converting and retargeting human demonstrations into robot-executable trajectories and actions
Collaborating directly with customers and stakeholders to understand requirements and deliver practical solutions
Writing clean, reproducible code and maintaining high engineering discipline across simulation codebases
Leading cross-functional teams and providing technical leadership on simulation strategy and roadmap
Documenting technical workflows and contributing to internal knowledge bases for simulation tools
Technology
The tools and technologies that define this role.
Open Jobs
34 open Simulation Engineer jobs across 14 companies.
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