Sensor Rendering Engineer (NVIDIA Omniverse)
Caterpillar
- Location
- Irving, Texas
- Work model
- On-Site
- Level
- Mid
- H-1B history
- 106 approvals (FY2023)
- Posted
- Aug 14, 2026
Skills
About this role
Career Area: Technology, Digital and Data Job Description: Your Work Shapes the World at Caterpillar Inc. When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it. Help Build the Future of Caterpillar – At Caterpillar, technology always has a purpose, which is to solve our customers’ toughest challenges. Through Cat Technology, we are solving problems by building the intelligence layer that connects machines, data, and people to make jobsites safer, more productive, and more sustainable. By combining deep domain expertise in physical systems with software, connectivity, autonomy, and AI, we deliver solutions that work in the real world—on real jobsites, at global scale. Be Part of What’s Next in Autonomous Construction Sites Construction autonomy is one of the most complex challenges in applied AI, and at Caterpillar, advancements in physical AI, simulation, sensing, and edge computing are turning things that once felt impossible—intelligent machines operating in dynamic jobsites—into reality. If this work motivates you, we invite you to join our team. Apply today to build the new era of construction autonomy at Caterpillar.
Role
Definition The Sensor Rendering Engineer is responsible for developing, validating, and optimizing high-fidelity sensor simulation and rendering capabilities within the NVIDIA Omniverse ecosystem. This role focuses on creating physically accurate virtual sensing environments that support robotics, autonomy, digital twin, and machine intelligence applications. The engineer collaborates closely with autonomy, perception, simulation, and visualization teams to ensure synthetic sensor data accurately represents real-world operating conditions and enables robust algorithm development, testing, and validation. Key areas of ownership include sensor modeling, rendering pipeline support, synthetic data generation, environmental realism, performance optimization, and the integration of camera, LiDAR, radar, and other virtual sensors into large-scale simulation environments. The role requires expertise in real-time rendering technologies, RTX-based ray tracing, Omniverse Isaac Sim, USD workflows, and sensor fidelity validation against real-world data. The ideal candidate combines strong software engineering skills with deep knowledge of computer graphics, physically based rendering, sensor physics, and simulation technologies to deliver scalable, accurate, and production-ready virtual sensing solutions.
Responsibilities
Develop and maintain high-fidelity sensor rendering solutions for camera, LiDAR, radar, depth, and other perception systems within NVIDIA Omniverse and Isaac Sim. Design, implement, and validate physically based sensor models that accurately represent real-world sensor behavior and environmental interactions. Create synthetic data generation pipelines to support machine learning, computer vision, perception, and autonomous system development. Optimize RTX-based rendering workflows to balance sensor accuracy, scalability, and simulation performance. Develop tools and automation frameworks for sensor configuration, calibration, testing, and data collection. Collaborate with autonomy, perception, controls, and digital twin teams to define sensor requirements and validation criteria. Build and maintain USD-based simulation assets, environments, and workflows that support enterprise-scale digital twin initiatives. Model environmental effects such as lighting, weather, dust, fog, material properties, occlusions, and surface reflectance to improve simulation realism. Correlate simulated sensor outputs with