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.
Measured across 24 of 34 open postings.
This role is advertised at one level, so a single figure for the role would describe none of them. Experience and pay are the midpoints for each level on its own.
| Level | Share | Median years | Median pay |
|---|---|---|---|
| Mid | 46%(11) | — | — |
A dash means too few postings stated it to report a midpoint at any level. Most companies do not publish a salary band, so pay is indicative rather than a market rate. 3 levels with fewer than 10 open postings are not shown.
“We use machine learning to model the real world, including realistic agents (vehicles, pedestrians, cyclists, motorcyclists etc.), roads, traffic control systems, and weather.”
“Combine simulation with deep learning for surrogate modeling, learned physics, inverse problems, parameter estimation, and optimization.”
“Develop the tooling that underpins RL training, including domain randomisation, to improve sim-to-real generalisation”
“Work at the intersection of CAE and data science to generate high-quality simulation datasets for training machine learning and deep learning surrogate models”
Skills
What companies are looking for in this role.
Simulation and physical modeling
Research experiment design
Research-to-production translation
ML systems development
Large-scale model training
Distributed systems architecture
Systems performance optimization
Model architecture design
Technical issue diagnosis
Data pipeline engineering
Model behavior analysis
Statistical modeling and uncertainty
Computer vision and perception
AI evaluation design
Embodied AI and sim-to-real
Inference performance optimization
Agentic system research
Technical documentation
Research rigor and reproducibility
Mentoring and code review
Technology
The tools and technologies that define this role.
Open Jobs
34 open Simulation Engineer jobs across 9 companies.
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