Business Needs Inc.
Lead Recruiter/Talent Acquisition Specialist || Full Recruitment Lifecycle
Job Description:
An Isaac Sim expert has deep knowledge of NVIDIA's robotics simulation platform
and its integration into robotics and AI workflows. This expertise covers building, testing, and training AI-driven robots in physically realistic virtual environments using the NVIDIA Omniverse platform.
Core areas of expertise
Physics simulation:
Tuning and optimizing the high-fidelity, GPU-accelerated PhysX engine for realistic robot behavior.
Synthetic data generation (SDG):
Using NVIDIA Omniverse Replicator to generate large, labeled datasets for training perception models. This includes randomizing scenes, objects, and lighting to create diverse data.
Digital twins:
Creating precise virtual replicas of real-world environments, such as factory floors, to design and validate robot applications before real-world deployment.
Robot learning:
Developing and accelerating reinforcement learning (RL) and imitation learning algorithms using the GPU-accelerated Isaac Lab framework.
Sensor simulation:
Accurately simulating a variety of sensors, including cameras, LiDAR, and contact sensors, with features like RTX real‑time ray and path tracing.
Robotics integration:
Bridging the simulation to real-world robots using communication protocols like ROS and ROS 2.
Workflow scripting:
Using Python and the Core API for a wide range of tasks, from building environments to scripting complex robot behaviors.
USD and Omniverse:
Leveraging the Universal Scene Description (OpenUSD) file format to import, build, and share robot and environment assets.
Key skills for an Isaac Sim expert Recruiters and project managers seeking an expert in this field often look for the following skills:
Technical proficiency:
Deep expertise in
Python and/or C++
and extensive experience with
Isaac Sim
and the
Omniverse platform .
Robotics fundamentals:
A strong background in physics,
kinematics, motion planning, and 3D modeling .
Machine learning:
Knowledge of training and
deploying AI models , particularly in the context of robot perception and control.
System integration:
Experience integrating different software components and hardware into a cohesive robotics system.
Troubleshooting:
The ability to debug complex issues related to physics, integration, and simulation performance.
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An Isaac Sim expert has deep knowledge of NVIDIA's robotics simulation platform
and its integration into robotics and AI workflows. This expertise covers building, testing, and training AI-driven robots in physically realistic virtual environments using the NVIDIA Omniverse platform.
Core areas of expertise
Physics simulation:
Tuning and optimizing the high-fidelity, GPU-accelerated PhysX engine for realistic robot behavior.
Synthetic data generation (SDG):
Using NVIDIA Omniverse Replicator to generate large, labeled datasets for training perception models. This includes randomizing scenes, objects, and lighting to create diverse data.
Digital twins:
Creating precise virtual replicas of real-world environments, such as factory floors, to design and validate robot applications before real-world deployment.
Robot learning:
Developing and accelerating reinforcement learning (RL) and imitation learning algorithms using the GPU-accelerated Isaac Lab framework.
Sensor simulation:
Accurately simulating a variety of sensors, including cameras, LiDAR, and contact sensors, with features like RTX real‑time ray and path tracing.
Robotics integration:
Bridging the simulation to real-world robots using communication protocols like ROS and ROS 2.
Workflow scripting:
Using Python and the Core API for a wide range of tasks, from building environments to scripting complex robot behaviors.
USD and Omniverse:
Leveraging the Universal Scene Description (OpenUSD) file format to import, build, and share robot and environment assets.
Key skills for an Isaac Sim expert Recruiters and project managers seeking an expert in this field often look for the following skills:
Technical proficiency:
Deep expertise in
Python and/or C++
and extensive experience with
Isaac Sim
and the
Omniverse platform .
Robotics fundamentals:
A strong background in physics,
kinematics, motion planning, and 3D modeling .
Machine learning:
Knowledge of training and
deploying AI models , particularly in the context of robot perception and control.
System integration:
Experience integrating different software components and hardware into a cohesive robotics system.
Troubleshooting:
The ability to debug complex issues related to physics, integration, and simulation performance.
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