Sensor Rendering Engineer (NVIDIA Omniverse)
$112,710–$183,140 year
On-siteIrving, Texas, United States
Job Summary
Develop and maintain high-fidelity sensor rendering solutions for camera, LiDAR, radar, and depth systems within NVIDIA Omniverse and Isaac Sim. Design, implement, and validate physically based sensor models that accurately represent real-world behavior, while creating synthetic data generation pipelines to support machine learning and autonomous system development. Optimize RTX-based rendering workflows to balance accuracy, scalability, and performance, and build automation frameworks for sensor configuration and testing. Correlate simulated outputs with real-world datasets to drive continuous model improvements and integrate capabilities into virtual machine validation frameworks. Model environmental effects such as lighting, weather, and material properties to enhance simulation realism, providing technical leadership in rendering technologies and sensor physics.
Required Qualifications
- Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, Robotics, Graphics Engineering, or a related technical discipline.
- 5+ years of experience in software development, simulation, computer graphics, rendering, robotics, or autonomous systems development.
- Strong proficiency in Python and C++ for developing simulation, rendering, and automation applications.
- Hands-on experience with NVIDIA Omniverse, Isaac Sim, USD (Universal Scene Description), and RTX-based rendering technologies.
- Deep understanding of physically based rendering (PBR), ray tracing, path tracing, and real-time graphics pipelines.
- Experience modeling and simulating perception sensors, including cameras, LiDAR, radar, depth sensors, and inertial measurement systems.
- Knowledge of sensor physics, sensor calibration, noise modeling, and environmental effects impacting perception systems.
- Experience developing synthetic data generation solutions for machine learning, computer vision, or autonomous systems applications.
- Strong understanding of 3D geometry, optics, image formation, photogrammetry, and computer vision fundamentals.
- Experience working with large-scale simulation environments and digital twin technologies.
- Familiarity with GPU programming concepts, rendering optimization, and performance analysis techniques.
- Experience integrating simulation platforms with robotics, autonomy, perception, or machine learning workflows.
- Proficiency with source control systems, CI/CD pipelines, and modern software engineering practices.
- Strong analytical, troubleshooting, and problem-solving skills.
- Demonstrated ability to work effectively in cross-functional teams involving software, autonomy, controls, perception, and simulation engineers.
- Excellent verbal and written communication skills, including the ability to communicate complex technical concepts to diverse audiences.
- This position requires the candidate to work full-time at the Irving, TX office (Dallas).
- Domestic relocation assistance is available for this position.
- Visa sponsorship is available with this position.
- This position requires working onsite five days a week.
- An offer of employment is conditioned upon the successful completion of a drug screen.
Desired Qualifications
- Master's or Ph.D. in Computer Graphics, Robotics, Computer Vision, Artificial Intelligence, or a related field.
- Experience developing digital twins for industrial, construction, mining, agricultural, or autonomous vehicle applications.
- Familiarity with ROS/ROS2, NVIDIA Cosmos, Isaac Lab, OpenUSD, and synthetic data frameworks.
- Experience validating virtual sensor models against real-world sensor datasets and field measurements.
- Knowledge of machine perception, sensor fusion, localization, mapping, and autonomous navigation systems.
- Experience with cloud-based simulation infrastructure and scalable compute environments.
- Demonstrated technical leadership and mentoring experience.
- Experience supporting end-to-end virtual validation programs for autonomous or intelligent machines.
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