requirements to implementation. Develop and deploy simulation logic and behavioral models governing machine and system behavior. Implement real‑time simulation algorithms, including kinematics, dynamics, and control‑system interactions. This includes integration of physics engines (e.g., PhysX, Omniverse Physics, or equivalent) to support realistic behavior and machine–environment interactions. Develop and execute model validation and verification plans, ensuring digital twins are accurate and numerically stable. Develop robust scene composition, data modeling and asset management approaches for engineering digital twins across component, blade, rack and facility-level views. Create high-fidelity 3D models, scenes and environments in Omniverse. Develop interfaces that connect simulations to real‑time visualization, dashboards, and operator‑focused experiences. Implement automated test pipelines and document model correlations, limitations, and validation scoring. Contribute to toolchain and pipeline design, including scripting utilities, automated test frameworks, and modular code libraries. Collaborate across data engineering/architecture, autonomy, product groups, and engineering to ensure interoperability and alignment with business needs. Evaluate and implement new simulation libraries and real‑time rendering technologies that enhance simulation fidelity and performance. Work hands‑on with multiple digital‑twin platforms, such as: NVIDIA Omniverse (primary environment), CARLA, Siemens NX/Teamcenter/Plant Simulation, Dassault 3DEXPERIENCE, Ansys Twin Builder, Unity or similar. Integrate engineering and operational data from simulation, test, telemetry, design systems, asset inventories and infrastructure sources into coherent digital twin environments. Support testing, debugging, performance analysis and reliability improvements across digital twin applications and services. Establish engineering best practices for OpenUSD schemas, Omniverse workflows, version control, documentation and release processes. Provide technical guidance, code review and mentoring to engineers working with digital twin, simulation and data integration technologies. Produce clear technical documentation and communicate progress, risks and decisions to technical and non-technical stakeholders. Candidate Profile Essential Degree in Mechanical, Electrical, Systems Engineering, Computer Science or related discipline. 8+ years of engineering experience in automation, simulation, or controls. Experience designing, building or maintaining digital twin, simulation, 3D visualization or engineering platform software. Hands-on experience with the Omniverse platform, including Omniverse Kit, extensions, connectors or related development workflows. Strong knowledge of OpenUSD / USD concepts, including composition, layering, schemas, assets and scene graph workflows. Experience working with data center operations, infrastructure environments, operational planning or systems used to manage complex technical facilities. Experience developing simulation or modeling workflows that support engineering decisions for complex hardware, infrastructure or operational systems. Strong software engineering skills in Python, C++ or both, with experience building maintainable production-quality tools or services. Experience integrating complex engineering and operational data from multiple systems, formats or APIs into usable software workflows. Understanding simulation, real-time visualization, physics-based modeling, rendering pipelines or spatial computing concepts. Ability to lead complex technical tasks independently, manage priorities and make sound engineering decisions with incomplete information. Strong collaboration and communication skills, with the ability to work effectively across multiple engineering disciplines. Experience reviewing designs and code, sharing technical knowledge and helping other engineers adopt new tools and practices. Desirable Experience applying digital twin technologies in data center, high-performance computing, semiconductor, robotics, manufacturing or complex systems environments. Experience with rack and blade design concepts, including physical layout, serviceability, power, cooling, cabling, networking or mechanical constraints. Experience modeling thermal, power, airflow, mechanical, cabling, networking or serviceability characteristics for rack-scale or facility-scale systems. Experience with synthetic data generation, sensor simulation, telemetry visualization or operational monitoring workflows. Knowledge of containerized deployment, cloud or on-premises infrastructure, CI/CD and automated testing for engineering tools. Experience with 3D asset pipelines, materials, lighting, rendering, physics simulation or model optimization. Familiarity with adjacent platforms or technologies such as Unreal Engine, Unity, Blender, ROS, CAD/CAE tools, DCIM tools or PLM systems. Understanding of AI, machine learning, accelerated computing or large-scale system architecture concepts. Experience developing user-facing tools for engineering or operations teams, including workflow design, usability improvements and technical enablement.
