英伟达Senior Software Engineer, Robotics
任职要求
• Master's degree or above in Robotics, Computer Science, Engineering, or a related field, or equivalent experience. • 5+ years of experience. • Skilled at robotic policy development workflow, from lab to launch: teleoperation, synthetic data generation, domain randomization, VLA and RL post-training, sim2real transfer, deployment with edge AI platforms. • Familiar with popular VLA and RL algorithms, co-working with robotics researchers to design robotic policy for specific tasks, especially healthcare scenes. • Proven experience in designing and building robotics software stacks. • Proficiency in Python, C++, PyTorch. Willingness to learn new languages and tools …
工作职责
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
NVIDIA is seeking a highly skilled and motivated Robotics Applied Research Software Engineer specializing in Sim2Real and Humanoid Loco-Manipulation to join our Robotics team. This role focuses on building software for developing and deploying robotic policies from simulation to real-world environments, creating data generation pipelines, and applying robot learning for robotics. The ideal candidate will have strong software engineering skills, applied research and engineering experience in robotics and machine learning, and expertise in PyTorch, C++, and Python. Real-world experience with humanoid robots, particularly in loco-manipulation, is highly preferred. What You Will Be Doing: • Perform Vision-Language-Action (VLA) pre-training and post-training. • Implement and enhance robot learning algorithms for robotics. • Deploy algorithms on real humanoid robots to evaluate sim2real transfer. • Focus on humanoid loco-manipulation tasks to advance robotic capabilities. • Collaborate with research and engineering teams to enable foundation models Sim2Real transfer on humanoid robots. • Run experiments and analyze results to improve robotic system performance. • Continuously learn and explore new technologies. • Cross team collaborations and leadership for sim2real efforts • Publish papers / technical reports for the applied research work.