英伟达Senior Software Engineer - Robotics Application
任职要求
NVIDIA’s robotics Isaac is a fast-progressing effort inside the company and will have a decisive impact on the future of the robotics industry, including on humanoid robots. We are looking for self-motivated and innovative candidates to investigate approaches to large-scale mobile manipulation problems.NVIDIA is searching for a passionate and creative Senior Software Engineer to help build the next generation of embodied AI using Isaac Lab and Mimic! This is a rare opportunity to join a world-class team pushing the boundaries of robotics simulation, control, and learning in physically grounded, high-fidelity virtual environments. You’ll work at the intersection of large-scale imitation learning, physics simulation, sim-to-sim and sim-to-real transfer — helping accelerate breakthroughs in generalizable robot behavior.
What You’ll Be Doing:
• Design and implement scalable data generation pipelines using Isaac Lab and Omniverse for learning dexterous, high-DOF robotic tasks.
• Extend and optimize NVIDIA’s Isaac Lab/Mimic toolchain for large scale learning from demonstration.
• Collaborate with research scientists on cutting-edge problems such as imitation learning, motion retargeting, manipulation, and loco-manipulation.
• Integrate large-scale, GPU-accelerated training workflows leveraging NVIDIA’s AI and simulation infrastructure.
• Develop modular and reusable environments for benchma…工作职责
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As a Senior Software Engineer on the NVIDIA Isaac projects, you will help build the platform for Physical AI robots — enabling sim-first development, real-world deployment, and continuous learning to make them smarter over time. The ideal candidate will have strong software engineering skills for real-time robotics applications and real-world experience with multi-body robots, such as humanoids and surgical robots. What You Will Be Doing: • Bring the latest advancements in Physical AI to simulated and real robots by building the runtime framework and healthcare industrial workflows, showcasing the power of NVIDIA's technology. • Collaborate across team boundaries to integrate NVIDIA robotics products such as Jetson Thor, Isaac GR00T, Holoscan, and Isaac Sim/Lab into the solution for robots. • Take on a variety of challenges, bridging between research and commercial environments. • Deploy and test the developed software on real robots.
Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error — this is truly an extraordinary time and the era of AI has begun. Image recognition and speech recognition — GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. The GPU started out as the engine for simulating human creativity, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA’s GPU runs Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and AI come together in our architecture. Two modes of the human brain, two modes of the GPU. This may explain why NVIDIA GPUs are used broadly for Deep Learning, and NVIDIA is increasingly known as “the AI computing company.” Make the choice to join us today. Our team builds NVIDIA’s end-to-end autonomous driving application.We are seeking senior software engineers who are passionate about performance with interest in optimizing self-driving solutions that run on NVIDIA’s multi-computer and heterogenous HW architectures. What you’ll be doing: • Develop, maintain and optimize performance KPIs necessary to deliver NVIDIA’s L2/L3/L4 autonomous driving solutions • Devise acceleration strategies and patterns to improve software architecture and its efficiency on our computers with multiple heterogeneous hardware engines while meeting or exceeding product goals • Develop highly efficient product code in C++, making use of algorithmic parallelism offered by GPGPU programming (CUDA)/ARM NEON while following quality and safety standards such as defined by MISRA • Diagnose and fix performance issues reported on our target platform including on-road & simulation