Senior Robotics Systems Engineer - Neural Reconstruction And Real2Sim Applications
at Nvidia
USD 152,000-287,500 per year
Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Machine Learning
Python @ 7
Robotics @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA's Isaac–NuRec team is building neural reconstruction and Real2Sim systems that turn real-world sensor data into high-fidelity, simulation-ready environments and objects for robotics simulation, learning, and deployment. As a Senior Systems Engineer, you will build dense 3D reconstruction systems, high-performance simulation workflows, and robotics software that bridge research innovations with production-grade systems, owning end-to-end pipelines that transform sensor streams into structured assets and environment representations for downstream robotic applications. We are looking for strategic, ambitious, and creative individuals passionate about advancing the boundaries of robotics!
Responsibilities
- Build end-to-end Real2Sim pipelines that ingest multi-modal sensor data (RGB/RGB-D, LiDAR, IMU) and produce high-fidelity scene and object representations for Isaac Sim.
- Develop neural 3D reconstruction systems and related 3D vision components to build digital twins of real-world environments and objects.
- Integrate reconstruction outputs with mapping, localization, and multi-sensor fusion systems for robust perception and navigation.
- Collaborate with ML researchers to integrate, deploy, and optimize workflows to enable training and validation in sim.
- Deploy and optimize reconstruction, data generation, and data augmentation pipelines at scale.
- Optimize, validate, and debug cross-stack systems spanning sensors, models, simulation, and downstream robot policies.
- Instrument and monitor production Real2Sim and reconstruction services, ensuring reliability, performance, and debuggability in large-scale deployments.
Requirements
- BS, MS, or PhD in Computer Science, Electrical Engineering, Robotics, or related field (or equivalent experience).
- 5+ years in robotics systems, 3D vision, simulation, or closely related software engineering roles.
- Hands-on experience with neural 3D reconstruction, mesh/object reconstruction, or deep-learning–based 3D vision.
- Exposure to reinforcement or imitation learning workflows for robotic perception and control.
- Experience with ROS 2 and real-time constraints, plus familiarity with Isaac Sim, Isaac Lab, or MuJoCo.
- Proven ability to drive technical direction or architecture for complex robotics or 3D perception systems, with strong Python and C++ skills and experience shipping production-quality systems.
Benefits
- You will also be eligible for equity and benefits.
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