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!
What you’ll be doing:
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.
What we need to see:
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.
Ways to stand out from the crowd:
Experience with neural scene representations (NeRF, 3D Gaussian Splatting, occupancy networks).
Experience with object reconstruction and sim‑ready asset generation pipelines (for example, mesh extraction, material and collision setup, USD export).
Familiarity with multi‑sensor fusion, sim‑to‑real transfer, and data augmentation workflows.
Experience building or integrating agentic frameworks, including LLM/VLM‑based task planners, tool‑use pipelines, or multi‑step reasoning systems.
Contributions to robotics or 3D vision open source, or publications at venues such as CVPR, ICCV, ICRA, RSS, or CoRL.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- 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
- Familiarity with Isaac Sim, Isaac Lab, or MuJoCo
- Proven ability to drive technical direction or architecture for complex robotics or 3D perception systems
- Strong Python and C++ skills and experience shipping production-quality systems
- Experience with neural scene representations (NeRF, 3D Gaussian Splatting, occupancy networks)
- Experience with object reconstruction and sim-ready asset generation pipelines (mesh extraction, USD export, material and collision setup)
- Familiarity with multi-sensor fusion, sim-to-real transfer, and data augmentation workflows
- Experience building or integrating agentic frameworks, LLM/VLM-based planners, or multi-step reasoning systems
- Open-source contributions or publications in robotics or 3D vision (CVPR, ICCV, ICRA, RSS, CoRL)
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
