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US, CA, Santa Clara

Internship

Onsite

Intern

NVIDIA is a leader in AI and simulation technology, and they are seeking a Software Engineering Intern for their Omniverse team. The role involves collaborating with simulation engineers and robotics researchers to deliver a simulation environment that accelerates robotics development and contributes to various projects related to Physical AI.

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Responsibilities

Work closely with simulation engineers, robotics researchers, and artists to define and deliver a simulation environment that accelerates robotics development
Support and collaborate with peers and leads on various projects related to Physical AI
Work on the Omniverse platform, including developer tooling, automation, cloud deployment, various runtimes, and content pipelines
Learn, test, and contribute to the developer SDKs and cloud APIs
You will help build production-quality software that:
Simulates, trains, and tests a range of robots and scales, from the edge to the cloud
Simulates various physical sensors (camera, lidar, IMU), vehicles, and rigid/soft-body dynamics
Generates synthetic data (segmentation, bounding boxes, etc.) for perception, navigation, and manipulation training at scale
Ensures transfer learning from simulation to physical robots
Provides a simulation environment for developing intelligent machines that work closely with people in a safe, collaborative manner

Qualification

Required

Pursuing a PhD, Master's, or Bachelor's degree in Computer Science, Applied Math, or a related field
Strong software development skills (C++, Python)
Experience working in large-scale code bases/ projects
A solid sense of software architecture
Experience building, supporting, or contributing to large-scale production software, particularly in 3D graphics, simulation, and distributed or cloud systems
Experience working with NVIDIA Omniverse, Isaac Sim, or USD
Hands-on experience with cloud infrastructure, especially Docker, Kubernetes, Rust, gRPC, REST API, and CI/CD systems
Experience implementing or using physics simulation systems (e.g., rigid body, deformable systems, etc.) in the context of robotics training or digital twin