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Modeling And Simulation Engineer Jobs in Berkeley, CA

Form Energy

Staff Thermal Simulation Engineer

Berkeley, CA · On-site

$147K - $221K/yr

Role Description As a Staff Simulation Engineer specializing in Computational Fluid Dynamics (CFD ... You will own the thermal-fluid architectural strategy, physics-based modeling framework, and multi ...

Slope

Simulation Infrastructure Engineer

San Francisco, CA · On-site

$170 - $210/hr

Working across the entire model stack, we integrate cutting-edge hardware and software to explore a ... About the Role We are hiring a Sim Infrastructure Engineer to turn simulation systems into reliable ...

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All JobsModeling And Simulation Engineer JobsModeling And Simulation Engineer Jobs in Berkeley, CA

Modeling And Simulation Engineer information

See Berkeley, CA salary details

$47.8K

$151.1K

$233.3K

How much do modeling and simulation engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for modeling and simulation engineer in Berkeley, CA is $151,095.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,600.00 and $179,400.00 per year, depending on experience, location, and employer.

What is a modeling and simulation engineer?

Modeling and Simulation Engineers are professionals who use mathematical models and computer simulations to analyze complex systems and predict their behavior. They work in various industries, including aerospace, defense, healthcare, and manufacturing, to improve product design, optimize processes, and support decision-making. Their work often involves creating virtual prototypes, running simulations to test different scenarios, and interpreting results to provide insights for engineering projects. These engineers typically have strong backgrounds in mathematics, physics, and computer science.

What are the key skills and qualifications needed to thrive as a modeling and simulation engineer?

To thrive as a Modeling and Simulation Engineer, you need a strong background in mathematics, physics, computer science, and engineering principles, typically supported by a relevant degree. Proficiency with simulation software (such as MATLAB, Simulink, or ANSYS), programming languages (like Python or C++), and sometimes certifications in modeling tools are highly valued. Analytical thinking, problem-solving, and effective communication are essential soft skills for translating complex systems into accurate models and collaborating with multidisciplinary teams. These skills are crucial for ensuring the accuracy, reliability, and usability of simulations that inform critical engineering decisions.

What are some common challenges a modeling and simulation engineer faces when integrating new models into existing systems?

A common challenge for Modeling and Simulation Engineers is ensuring that new models are compatible with existing simulation frameworks and data sources. This often involves resolving discrepancies in data formats, model fidelity, and simulation timing, as well as validating that the integrated system produces accurate and reliable results. Collaboration with software developers, data analysts, and subject matter experts is essential to troubleshoot integration issues and maintain system performance. Effective communication and thorough documentation are key to overcoming these integration hurdles.

What is the difference between Modeling And Simulation Engineer vs Systems Engineer?

AspectModeling And Simulation EngineerSystems Engineer
CredentialsBachelor's or Master's in Engineering, Computer Science, or related fields; certifications like INCOSEBachelor's or Master's in Engineering, Systems Engineering, or related fields; certifications like INCOSE
Work EnvironmentDesigning and developing simulation models, testing scenarios in labs or software environmentsIntegrating system components, coordinating across engineering teams, often in project offices
Industry UsageDefense, aerospace, automotive, and manufacturing sectorsDefense, aerospace, IT, and complex system development industries

While both roles require engineering backgrounds and similar certifications, Modeling And Simulation Engineers focus on creating and testing simulation models, whereas Systems Engineers oversee the integration and functionality of entire systems. Both collaborate closely but serve different specialized functions within engineering projects.

Are modeling and simulation engineers in demand?

Modeling and simulation engineers are in high demand across industries such as aerospace, defense, automotive, and healthcare due to their expertise in developing complex models and simulations. The role often requires proficiency in programming, simulation software, and systems analysis, with job growth driven by technological advancements and increased reliance on virtual testing and training tools.

How to become a modeling and simulation engineer?

To become a modeling and simulation engineer, typically a bachelor's degree in engineering, computer science, or a related field is required, often complemented by experience with simulation software, programming languages, and systems modeling. Advanced roles may require a master's degree or higher, along with skills in data analysis, systems engineering, and familiarity with tools like MATLAB, Simulink, or C++. Certifications in systems modeling or simulation can enhance job prospects.

What are popular job titles related to Modeling And Simulation Engineer jobs in Berkeley, CA?

For Modeling And Simulation Engineer jobs in Berkeley, CA, the most frequently searched job titles are:

What job categories do people searching Modeling And Simulation Engineer jobs in Berkeley, CA look for?

The top searched job categories for Modeling And Simulation Engineer jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Modeling And Simulation Engineer jobs?

Cities near Berkeley, CA with the most Modeling And Simulation Engineer job openings:

Modeling And Simulation Engineer jobs near you
Infographic showing various Modeling And Simulation Engineer job openings in Berkeley, CA as of August 2026, with employment types broken down into 92% Full Time, 4% Part Time, and 4% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $151,095 per year, or $72.6 per hour.

Member of Technical Staff - Simulation Engineer

Moonlake AI

San Francisco, CA • On-site

Full-time

Re-posted 2 days ago

Key responsibilities

  • Design and develop simulation environments for robotics training and evaluation

  • Build simulation systems supporting perception, navigation, manipulation, and embodied AI tasks

  • Develop infrastructure supporting large-scale synthetic data generation and improve simulation workflows

Job description

Introducing Moonlake, AI for creating world simulations.
About Moonlake
Moonlake is building the frontier of interactive world models: systems that generate, simulate, and reason over 3D environments for robotics, embodied AI, and interactive applications.
We develop the infrastructure that enables intelligent systems to learn, evaluate, and interact within realistic virtual environments before operating in the physical world.
Our work sits at the intersection of:
  • Robotics
  • Embodied AI
  • Interactive 3D Worlds
  • World Models
  • Simulation Infrastructure
  • Physical AI

Moonlake is building the next generation of AI infrastructure for interactive digital worlds. Our mission is to enable anyone to create, simulate, and interact with rich environments using natural language and multimodal inputs, turning simple ideas into worlds with structure, physics, and intelligent behavior.
Our team has raised $28M in seed funding from NVIDIA Ventures, Threshold Ventures, AIX Ventures, and notable angels including Naval Ravikant and Jeff Dean to build the foundational layer for the future of AI-powering everything from robotics training and simulation to digital twins and interactive environments.
We are looking for exceptional engineers to help build the simulation systems that will power the next generation of robotics and embodied intelligence.
The Role
We're looking for a Member of Technical Staff - Simulation Engineer to build the simulation systems and infrastructure that power robotics and embodied AI.
This role focuses on developing high-fidelity simulation environments that accurately model robot behavior, sensors, physics, and real-world interactions. You'll build the simulation infrastructure used for robot learning, evaluation, synthetic data generation, and sim-to-real transfer.
You'll collaborate closely with teams working on robotics, world models, AI systems, and simulation infrastructure.
This is a highly hands-on software engineering role for builders who enjoy solving challenging problems across robotics, simulation, physics, and distributed systems.
What You'll Do
Build Robotics Simulation Systems
  • Design and develop simulation environments for robotics training and evaluation
  • Build simulation systems supporting perception, navigation, manipulation, and embodied AI tasks
  • Develop scalable simulation workflows that enable rapid experimentation and robot learning
  • Build reusable tooling that makes simulation development efficient and reliable
Improve Sim-to-Real Transfer
  • Compare simulation outputs against real-world robot behavior
  • Model robot dynamics, sensors, contacts, and environmental interactions
  • Tune simulation fidelity through calibration and validation
  • Improve policy transfer using calibration, benchmarking, and domain randomization techniques
Support Robot Learning
  • Partner with robotics and AI teams to build environments for training and evaluating intelligent systems
  • Develop infrastructure supporting large-scale synthetic data generation
  • Create simulation benchmarks for evaluating robotics models
  • Optimize simulation environments for machine learning workflows
Build Simulation Infrastructure
  • Develop production-quality software supporting simulation systems
  • Build tools that improve simulation reliability, testing, and scalability
  • Improve pipelines for simulation creation, execution, and evaluation
  • Optimize simulation performance while maintaining physical realism
Areas of Focus
Robotics Simulation
  • Physics simulation
  • Robot dynamics
  • Sensor simulation
  • Sim-to-real transfer
  • Robot learning environments
Simulation Infrastructure
  • Synthetic data generation
  • Simulation tooling
  • Environment automation
  • Performance optimization
  • Benchmarking and validation
Robotics
  • Perception
  • Manipulation
  • Navigation
  • Embodied AI
  • Physical reasoning
What We're Looking For
  • Experience building robotics simulation systems for robotics, autonomy, embodied AI, or physical AI
  • Experience with robotics simulators such as Isaac Sim, MuJoCo, PyBullet, Gazebo, Drake, or equivalent
  • Understanding of robot dynamics, physics simulation, sensor modeling, and sim-to-real transfer
  • Strong software engineering skills in Python, C++, or similar languages
  • Experience building production-quality simulation software and infrastructure
  • Experience writing reliable, maintainable, and well-tested code
  • Strong systems thinking and problem-solving skills
  • Ability to work closely with robotics, machine learning, and research teams
Nice to Have
  • Experience with NVIDIA Isaac Sim or Omniverse
  • Experience generating synthetic data for robotics or machine learning
  • Experience with domain randomization or procedural environment generation
  • Familiarity with ROS2 and modern robotics software stacks
  • Experience optimizing simulation performance or GPU-accelerated simulation
  • MS or PhD in Robotics, Computer Science, Mechanical Engineering, or a related field
Why This Role Matters
Moonlake's vision depends on simulation systems that allow intelligent agents to learn, evaluate, and improve before operating in the physical world.
The quality of our world models, robotics systems, and AI infrastructure depends on simulation environments that are physically accurate, computationally efficient, and scalable.
As a Simulation Engineer, you'll build the core simulation infrastructure that powers the next generation of robotics and embodied AI.
We are committed to being an on-site, in-person team currently based in San Francisco.

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