Senior Software Engineer (Digital Twin)

Your Mission

HMGICS serves as the core manufacturing testbed for the Hyundai Motor Group, focused on creating a cutting-edge, software-defined factory for autonomous and flexible production of future mobility solutions. Within the Technology Innovation Group, the Software & Data Engineering Team develops intelligent systems and environments (IoT, MLOps, Visualization, and Simulations) to drive factory transformation initiatives and future autonomous operations.

We are seeking a Senior Software Development Engineer specializing in Digital Twin and Simulation. In this role, you will design, develop, deploy, and maintain scalable software solutions that enable digital twin applications across manufacturing, logistics, and industrial automation domains.

As a senior member of the team, you will bridge simulation engineering, software development, and enterprise infrastructure, helping translate industrial engineering requirements into robust, production-ready applications and platforms based on NVIDIA Omniverse and OpenUSD technologies. You will contribute hands-on to software architecture, system integration, platform deployment, and the continuous evolution of HMGICS' digital twin capabilities.

What To Expect

Digital Twin Platform & Application Development

• Design and implement scalable digital twin and simulation applications using NVIDIA Omniverse and Kit-based technologies.
• Develop reusable Omniverse extensions, tools, services, and APIs supporting digital twin workflows across multiple use cases.
• Contribute to software architecture, technical standards, and platform capabilities, ensuring scalability and maintainability.
• Lead technical design reviews and contribute to architecture decisions within the team.

OpenUSD & Data Integration

• Develop and maintain OpenUSD-based asset pipelines, ensuring interoperability between CAD tools and simulation environments.
• Support the management of USD assets, compositions, layers, and variants for large-scale digital twin environments.
• Work closely with 3D artists and asset teams to ensure technical correctness and performance.
• Develop data ingestion and synchronization pipelines connecting digital twins with engineering and operational systems.

Simulation

• Collaborate with automation engineering, production, and logistics teams to digitize and validate factory processes and workflows.
• Support the development of simulation applications used for virtual commissioning, production planning, logistics analysis, process validation, and operational optimization.
• Contribute to defining modeling approaches, assumptions, and validation methodologies for digital twin applications.
• Support the integration of simulation results into business and engineering decision-making processes.
• System Integration and Platform Operation
• Design and support deployment architectures for on-premises digital twin platforms using NVIDIA Omniverse and related technologies.
• Develop integrations with enterprise applications, IIoT platforms, MES, databases, and external APIs.
• Collaborate with IT teams on infrastructure planning, security, deployment, and operational best practices.
• Support containerized deployment strategies and platform scalability.
• Contribute to performance optimization, monitoring, reliability, and maintainability of deployed solutions.

Leadership, Collaboration & Continuous Improvement

• Connect and collaborate with teams across regions to share best practices and contribute to global standards definition.
• Interface and collaborate with multiple corporate functions to define technical requirements and prepare presentations and reports.
• Contribute to technical documentation, coding standards, architecture guidelines, and team playbooks.
• Provide technical guidance and mentorship through design discussions, code reviews, and hands-on collaboration.
• Stay current with emerging technologies related to digital twins, OpenUSD, industrial software systems, simulation, and AI.

What You'll Bring

• Bachelor's, Master's, or PhD degree in Computer Science, Software Engineering, Industrial Engineering, Mechanical Engineering, Robotics, or a related discipline.
• 5+ years of relevant industry experience in software development, simulation platforms, digital twins, robotics, industrial software systems, or related domains; alternatively, a PhD with relevant research or industry experience in these fields.
• Strong programming skills in Python and experience developing maintainable, production-quality software.
• Experience developing applications, tools, APIs, or integrations within complex software ecosystems.
• Hands-on experience with NVIDIA Omniverse, OpenUSD, or similar industrial 3D/simulation platforms.
• Experience integrating software systems with databases, enterprise applications, web services, or industrial platforms.
• Experience with manufacturing, logistics, industrial engineering, or factory operations.
• Experience with OpenUSD, USD compositions, variants, and asset management workflows.
• Experience deploying containerized applications in Kubernetes-based environments.
• Familiarity with GPU-enabled infrastructure supporting simulation, visualization, or AI workloads.
• Experience with cloud-native or hybrid deployment architectures.
• Experience with robotics, ROS/ROS2, or industrial automation systems.
• Experience integrating AI/ML techniques into industrial software workflows, including synthetic data generation, surrogate models, reduced-order models, and reinforcement learning.
• Experience with NVIDIA Cloud Functions (NVCF) or other enterprise Omniverse deployment patterns.
• Hands-on experience with simulation tools such as Siemens Plant Simulation, AnyLogic, FlexSim, Simio, or related environments.
• Experience with physics-based modeling and simulation methodologies, including finite element analysis (FEA/FEM), computational mechanics, multibody dynamics, material modeling, deformable body simulation, or related domains.
• Prior experience in automotive, manufacturing, logistics, or industrial engineering domains.
• Strong analytical and problem-solving skills.
• Ability to work effectively within multidisciplinary engineering teams.
• Excellent technical documentation skills.