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Digital Twin Simulation Model Jobs (NOW HIRING)

Actalent

Controls Simulation Engineer

Warren, MI · Hybrid

$45 - $50/hr

Develop and update the Throughput Discrete Event Simulation (DES) Digital Twin model in line with current GA Manufacturing Operations design. * Monitor the DES Digital Twin performance, identify ...

Hammerhead AI

Simulation Engineer

Redwood City, CA · On-site

$100 - $130/hr

Key Responsibilities * Digital Twin Development: Architect and build high‑fidelity ... Model Validation: Develop methodologies to validate simulation accuracy against real‑world ...

Epoch Biodesign

Simulation Engineer

Redwood City, CA · On-site

$100 - $130/hr

Key Responsibilities * Digital Twin Development: Architect and build high‑fidelity ... Model Validation: Develop methodologies to validate simulation accuracy against real‑world ...

Leidos

Digital Engineer

Beavercreek, OH

$107K - $195K/yr

Apply systems engineering, systems modeling, product lifecycle management, and related techniques ... Experience with digital thread, digital twin, simulation environments, and enterprise-level data ...

Via Logic LLC

Digital Engineer

Beavercreek, OH · On-site

$107.90 - $195.05/hr

Apply systems engineering, systems modeling, product lifecycle management, and related techniques ... Experience with digital thread, digital twin, simulation environments, and enterprise-level data ...

Leidos

Digital Engineer

Beavercreek, OH · On-site

$107K - $195K/yr

Apply systems engineering, systems modeling, product lifecycle management, and related techniques ... Experience with digital thread, digital twin, simulation environments, and enterprise-level data ...

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Digital Twin Simulation Model information

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$39K

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$144K

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

As of Sep 5, 2026, the average yearly pay for digital twin simulation model in the United States is $101,255.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,500.00 and $129,500.00 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.

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Digital Twin Simulation Model jobs near you
Infographic showing various Digital Twin Simulation Model job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 89% Physical, 3% Hybrid, and 8% Remote job distribution, with an average salary of $101,255 per year, or $48.7 per hour.

Staff Engineer - AI/ML & Digital Twin

Synopsys Inc

Canonsburg, PA • On-site

Full-time

Re-posted 5 days ago

Job description

Job Summary:
Synopsys Inc, part of Ansys, is a global leader in engineering simulation software. They are seeking a Staff Engineer with expertise in AI/ML and digital twin technologies to lead technical engagements and develop innovative solutions that enhance engineering workflows and democratize simulation technology.
Responsibilities:
• Lead and execute technical engagements across the customer lifecycle, including discovery, solution development, demonstrations, evaluations, and deployment.
• Engage directly with customers to understand engineering workflows, data availability, and decision-making processes, translating them into AI-enabled simulation and digital engineering solutions.
• Develop and implement differentiated solutions using technologies such as automation, reduced order modeling, optimization, simulation democratization, system-level modeling, and digital twins.
• Integrate machine learning models within simulation and digital twin pipelines to improve prediction accuracy, reduce computational cost, and enable near real-time insights.
• Define and deliver automated and scalable workflows that reduce reliance on expert-driven simulation and enable broader adoption across engineering teams.
• Lead or contribute to first-of-a-kind or ambiguous use cases, including AI-assisted design exploration, surrogate modeling, and digital twin deployment.
• Collaborate closely with product development teams to influence roadmap, validate new capabilities, and improve usability of AI-enabled features.
• Deliver professional services, training, and technical guidance to ensure successful adoption of advanced workflows.
• Support pre-sales and technical marketing activities through demonstrations, evaluations, and industry engagement.
• Mentor team members and contribute to the best internal practices around AI, automation, and simulation integration.
Qualifications:
Required:
• MS (or PhD) in Engineering, Computer Science, Applied Mathematics, or related field.
• 5+ years of experience in engineering systems, simulation, or data-driven modeling.
• Strong programming skills (Python preferred).
• Experience working with modeling, simulation, optimization, or data-driven engineering workflows.
• Strong analytical, problem-solving, and communication skills.
• Ability to operate effectively in a customer-facing, consultative engineering role.
• Proven experience in automation of engineering workflows or pipelines using tools such as optiSLang, modeFrontier, HEEDS or equivalent.
• Demonstrated expertise applying machine learning techniques in engineering contexts, including surrogate modeling, regression methods, or neural networks (CNNs, RNNs, autoencoders).
• Understanding of projection-based ROMs, dimensionality reduction, and feature engineering.
• Knowledge of multi-fidelity system modeling using Twin Builder, Simulink, AMESim or equivalent.
• Familiarity with deployment and operationalization of AI models, including integration into engineering workflows and use of frameworks such as PyTorch, TensorFlow, scikit-learn, Kubernetes, AWS/Azure equivalent.
• Exposure to cloud or HPC-based environments for large-scale simulation or data processing.
Company:
Synopsys is the leader in engineering solutions from silicon to systems, enabling customers to rapidly innovate AI-powered products. Founded in 1986, the company is headquartered in Mountain View, USA, with a team of 10001+ employees. The company is currently Late Stage.
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About Synopsys

Sourced by ZipRecruiter

Synopsys, Inc. (Nasdaq:SNPS) is the Silicon to Software partner for creative companies developing the electronic products and software applications we rely on every single day. As the world's 15th largest software company, Synopsys has a long history of being a global leader in electronic design automation (EDA) and semiconductor IP and is also growing its leadership in software quality and security solutions. Whether you're a system-on-chip (SoC) designer building advanced semiconductors, or a software developer writing applications that require the highest quality and security, Synopsys has the solutions needed to deliver exceptional, secure products for the era of connected everything. The company is headquartered in Mountain View, California, and has approximately 113 offices located throughout North America, South America, Europe, Japan, Asia and India. Since 1986, Synopsys has been at the heart of accelerating electronics innovation with engineers around the world having used Synopsys technology to successfully design and create billions of chips and systems that are found in the electronics that people rely on every single day.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

Mountain View, CA, US

Year founded

1986

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