Robotics Simulation Architect - Physical AI & Pipelines

NVIDIA Corporation; Santa Clara (CA); On-site; USD 152,000 - 288,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA Corporation is seeking a hands-on Solutions Architect to advance robotics simulation, manipulation, and data generation. You will translate research into real-world workflows, collaborating across NVIDIA Research, Engineering, Product, and customers to scale AI-enabled simulation and sim-to-real deployment.

You will lead technical evaluations, build reference implementations, and optimize end-to-end pipelines spanning physics, rendering, data movement, and ML workflows.

Qualifications

• 5+ years hands-on experience building robotics simulation applications.
• Deep expertise with Isaac Sim, MuJoCo, Gazebo, or Drake, and core simulation domains.
• Familiarity with ROS 2 and robotics description formats such as OpenUSD, URDF, or MJCF.
• Proficiency in Python or C++, with API integration and distributed systems skills.
• Understanding GPU-accelerated computing applied to robotics simulation and ML workflows.

Responsibilities

• Work with robotics partners to adopt, extend, and scale NVIDIA's simulation technologies.
• Build and optimize workflows spanning rigging, physics, rendering, sensor simulation, and data generation.
• Diagnose bottlenecks across simulation, rendering, data movement, and large-scale workloads.
• Lead evaluations, PoCs, workshops, and reference implementations for platform adoption.
• Collaborate with engineering, product, and customers to shape roadmaps and guidelines.

Skills

Robotics

Python

C++

ROS 2

Education

BS/MS/PhD in Robotics/CS/ME/EE

Tools

Isaac Sim

MuJoCo

Gazebo

Drake

OpenUSD

URDF

Job description

NVIDIA Corporation is seeking a hands-on Solutions Architect to advance robotics simulation, manipulation, and data generation. You will translate research into real-world workflows, collaborating across NVIDIA Research, Engineering, Product, and customers to scale AI-enabled simulation and sim-to-real deployment.

You will lead technical evaluations, build reference implementations, and optimize end-to-end pipelines spanning physics, rendering, data movement, and ML workflows.