NVIDIA Omniverse Robotics Engineer

15 hours ago


Pune, Maharashtra, India Quest Global Full time ₹ 20,00,000 - ₹ 25,00,000 per year

Job Requirements

At Quest Global, it's not just what we do but how and why we do it that makes us different. With over 25 years as an engineering services provider, we believe in the power of doing things differently to make the impossible possible. Our people are driven by the desire to make the world a better place—to make a positive difference that contributes to a brighter future. We bring together technologies and industries, alongside the contributions of diverse individuals who are empowered by an intentional workplace culture, to solve problems better and faster.

Key Responsibilities

We are known for our extraordinary people who make the impossible possible every day. Questians are driven by hunger, humility, and aspiration. We believe that our company culture is the key to our ability to make a true difference in every industry we reach. Our teams regularly invest time and dedicated effort into internal culture work, ensuring that all voices are heard.

We wholeheartedly believe in the diversity of thought that comes with fostering a culture rooted in respect, where everyone belongs, is valued, and feels inspired to share their ideas. We know embracing our unique differences makes us better, and that solving the worlds hardest engineering problems requires diverse ideas, perspectives, and backgrounds. We shine the brightest when we tap into the many dimensions that thrive across over 21,000 difference-makers in our workplace.

Work Experience

We are seeking a skilled and experienced NVIDIA Omniverse Engineer with a focus on robotics simulation and digital twin creation. The ideal candidate will have hands-on experience using the NVIDIA Isaac sim and Isaac Lab platforms to build, simulate, and train robotic systems. This role requires expertise in creating virtual environments, importing and configuring robot models (including URDFs), and integrating with the Robot Operating System (ROS) for navigation and control tasks.

Responsibilities:

  • Design and build highly realistic and dynamic virtual environments within the NVIDIA Omniverse platform using USD Composer.
  • Develop digital twins of real-world industrial and robotics systems, replicating their behavior for simulation and testing.
  • Create, modify, and integrate robot models using the Unified Robot Description Format (URDF) into Isaac Sim and other Omniverse applications.
  • Utilize NVIDIA Isaac Sim to configure and run physics-accurate simulations, including simulating real-world processes like the movement of conveyor belts.
  • Apply NVIDIA Isaac Lab to accelerate reinforcement learning (RL) tasks for robotics by leveraging GPU-accelerated physics and a high-performance training pipeline.
  • Develop and implement ROS-based navigation stacks for obstacle avoidance, path planning, and localization within simulated environments.
  • Analyze and replicate the working principles of conveyor belts and other industrial machinery to create accurate digital twins for optimizing automation workflows.
  • Collaborate with AI, controls, and software teams to integrate simulated results with physical robotic hardware (Sim-to-Real).

Skills and Qualifications:

  • Proven experience with NVIDIA Omniverse, specifically Isaac Sim and Isaac Lab.
  • Proficiency in creating and editing 3D environments and assets using USD Composer.
  • Strong understanding of USD (Universal Scene Description) and USD-based workflows.
  • Expertise in creating and working with URDFs for various types of robot configurations.
  • Experience with the ROS framework, including the navigation stack and its core components (e.g., costmaps, planners).
  • Solid knowledge of robotics fundamentals, including kinematics, dynamics, and sensor integration.
  • Strong programming skills in Python for scripting, automation, and custom extension development within Omniverse.
  • Familiarity with the mechanical and operational principles of industrial automation components, such as conveyor belt systems.
  • Experience with simulation-based AI training, including reinforcement learning (RL).
  • Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.


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