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Digital Twin Simulation Model Jobs in California

Aveva

Director, Global Lead, PI and Digital Twin

Lake Forest, CA · On-site +1

$168K - $281K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Drive Digital Twin, AI strategic pillars with PI DI. * PI + AVEVA Software Depth The practice ... Must have PI system architecture and integration experience (PI to cloud, PI AF modeling, PI ...

Aveva

Director, Global Lead, PI and Digital Twin

San Leandro, CA · On-site +1

$168K - $281K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Drive Digital Twin, AI strategic pillars with PI DI. * PI + AVEVA Software Depth The practice ... Must have PI system architecture and integration experience (PI to cloud, PI AF modeling, PI ...

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All JobsDigital Twin Simulation Model JobsDigital Twin Simulation Model Jobs in California

Digital Twin Simulation Model information

See California salary details

$38.5K

$99.9K

$142.1K

How much do digital twin simulation model jobs pay per year?

As of Aug 17, 2026, the average yearly pay for digital twin simulation model in California is $99,929.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,500.00 and $127,800.00 per year, depending on experience, location, and employer.

What is a digital twin simulation model?

A Digital Twin Simulation Model is a virtual representation of a physical object, process, or system that is used to simulate, predict, and optimize its real-world counterpart. By using real-time data and advanced analytics, digital twins help organizations monitor performance, detect issues, and test scenarios without impacting actual operations. These models are widely used in industries such as manufacturing, healthcare, and smart cities to improve efficiency, reduce costs, and enable better decision-making.

What are common challenges faced when developing digital twin simulation models, and how can they be addressed?

One common challenge in developing digital twin simulation models is ensuring accurate data integration from various sources, which is crucial for creating realistic and actionable simulations. Team members often need to collaborate closely with engineers, IT specialists, and data analysts to validate and synchronize real-world and simulated data. Addressing these challenges requires strong communication skills, familiarity with integration tools, and a proactive approach to troubleshooting discrepancies. Additionally, keeping up with rapidly evolving technologies in simulation software and IoT devices is essential for maintaining effective and up-to-date models.

What are the key skills and qualifications needed to thrive as a digital twin simulation modeler, and why are they important?

To thrive as a Digital Twin Simulation Modeler, you need a solid background in engineering, computer science, or data science, along with experience in simulation modeling and systems analysis. Familiarity with tools like MATLAB, Simulink, Python, and specialized digital twin platforms (such as Siemens NX or PTC ThingWorx), plus relevant certifications, is often expected. Strong problem-solving abilities, communication, and collaboration skills help in translating real-world processes into accurate virtual models and working with cross-functional teams. These capabilities are crucial to create effective, scalable, and reliable digital twins that drive innovation and operational efficiency.

What is the difference between Digital Twin Simulation Model vs Data Analyst?

AspectDigital Twin Simulation ModelData Analyst
Required CredentialsEngineering, Computer Science, or related technical degrees; certifications in simulation or modelingStatistics, Data Science, or related degrees; certifications in data analysis tools
Work EnvironmentIndustrial, manufacturing, or engineering settings; using simulation softwareOffice or remote; analyzing datasets and creating reports
Industry UsageManufacturing, aerospace, energy, and infrastructureFinance, marketing, healthcare, and technology sectors
Search & Comparison IntentUnderstanding simulation modeling for system optimizationAnalyzing data trends and insights

The Digital Twin Simulation Model focuses on creating virtual replicas of physical systems for testing and optimization, often requiring engineering expertise. In contrast, Data Analysts interpret data to inform business decisions, typically using statistical tools. While both roles involve data and modeling, their applications and environments differ significantly.

What are popular job titles related to Digital Twin Simulation Model jobs in California?

For Digital Twin Simulation Model jobs in California, the most frequently searched job titles are:

What job categories do people searching Digital Twin Simulation Model jobs in California look for?

The top searched job categories for Digital Twin Simulation Model jobs in California are:

What cities in California are hiring for Digital Twin Simulation Model jobs?

Cities in California with the most Digital Twin Simulation Model job openings:

Digital Twin Simulation Model jobs near you
Infographic showing various Digital Twin Simulation Model job openings in California as of August 2026, with employment types broken down into 2% As Needed, 81% Full Time, 13% Part Time, 2% Temporary, and 2% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $99,929 per year, or $48 per hour.

Senior Staff Digital World System Engineer

XPENG

Santa Clara, CA • On-site

Full-time

Re-posted 25 days ago

Job description

Job Summary:
XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles. They are seeking a Senior Staff Digital World System Engineer responsible for the architecture design and technological evolution of synthetic data and Digital World generation systems, while collaborating with various teams to enhance the integration of synthetic and real data systems.
Responsibilities:
• Be responsible for the overall architecture design and technological evolution of the next-generation synthetic data and Digital World generation system, supporting large-scale model training, simulation and evaluation in the directions of autonomous driving, robotics and embodied intelligence.
• Lead the construction of core capabilities in directions such as Digital City, Digital Twin, and World Model, and build a high-fidelity, highly scalable virtual world generation and closed-loop simulation system.
• Be responsible for the R&D of algorithms and systems related to 3D/4D scene reconstruction, including multi-view 3D reconstruction, Gaussian Splatting, NeRF, SLAM/SfM, spatiotemporal scene modeling and other directions, to build large-scale spatial understanding and reconstruction capabilities.
• Build a synthetic data production engine for perception, prediction, planning, VLA and robot model training, realizing high-quality, high-efficiency and low-cost data generation and delivery.
• Explore the application of cutting-edge technologies such as Generative AI, Diffusion, World Model and Physics Simulation in the field of simulation and data generation, and promote the evolution of data closed-loop towards automation and intelligence.
• Build a closed-loop simulation system for Digital City, realizing capabilities such as problem scenario reproduction, model playback verification, long-tail problem mining and automated evaluation.
• Collaborate in depth with teams of autonomous driving algorithms, robotics, simulation platforms, data Infra and training platforms to promote the integration and large-scale application of synthetic data and real data systems.
• Define synthetic data quality standards and evaluation systems, continuously optimize authenticity, diversity, generalization and Sim2Real effects, and improve the benefits of model training.
• Be responsible for the construction of synthetic data platform and team, promote the platformization, engineering and large-scale landing of core technologies, and form long-term evolution capabilities.
Qualifications:
Required:
• Master's degree or above in Computer Science, Artificial Intelligence, Robotics, Computer Vision, Computer Graphics or related majors.
• Have R&D experience in related fields such as synthetic data, simulation systems, 3D vision, neural rendering or embodied intelligence.
• In-depth understanding of technologies related to 3D reconstruction and spatial modeling, including but not limited to SfM, SLAM, NeRF, Gaussian Splatting, Differentiable Rendering, Photogrammetry and other directions.
• Familiar with cutting-edge technology directions such as multi-modal large models, World Model, Generative AI, Diffusion and Reinforcement Learning, and have an in-depth understanding of data-driven model training systems.
• Have R&D experience in large-scale distributed systems, data generation platforms or high-performance rendering systems, and be able to promote the engineering landing of complex systems.
• Have excellent system architecture capabilities and cross-team collaboration capabilities, and be able to promote complex technical projects from research to production landing.
• Have continuous enthusiasm and technical exploration capabilities in directions such as embodied intelligence, World Model and Digital World generation.
Preferred:
• Candidates with relevant project experience in Digital Twin, Digital City, simulation platforms or large-scale virtual scene generation are preferred.
• Candidates familiar with Unreal Engine, Unity, Omniverse, physical simulation engines or graphics rendering pipelines are preferred.
Company:
XPENG is a leading Chinese Smart EV company that designs, develops, manufactures, and markets Smart EVs that appeal to the large and growing base of technology-savvy middle-class consumers. Founded in 2014, the company is headquartered in Guangzhou, CHN, with a team of 10001+ employees. The company is currently Late Stage.

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