英伟达Machine Learning Intern, Humanoid Loco-Manipulation - 2026
任职要求
• Currently enrolled in a PhD or Master’s program in Computer Science, Electrical Engineering, Robotics, or a related field, and available for the duration of the internship. • Strong programming skills in Python and C++; familiarity with deep learning frameworks (PyTorch, JAX, TensorFlow) and physics simulation tools (Isaac Sim/Lab, MuJoCo). • Demonstrated research or internship experience, with publications in top conferences. • Excellent communication and collaboration skills. • Experience with large-scale mo…
工作职责
The NVIDIA Isaac Loco-Manipulation team is seeking exceptional machine learning Interns to join our world-class robotics initiatives. As an intern, you’ll work alongside industry-leading experts, gaining hands-on experience and contributing to the future of humanoid loco-manipulation. We’re looking for strategic, ambitious, and creative individuals who are passionate about pushing the boundaries of robotics. What You’ll Be Doing: • Collaborate with researchers and engineers to define and execute projects focused on humanoid loco-manipulation and mobile manipulation. • Contribute to GR00T and Cosmos foundation models. • Support the development of reference workflows in Isaac Lab and Newton. • Advance technologies for robot learning and synthetic data generation using human video datasets. • Design, implement, and deploy novel algorithms for humanoid robot locomotion and manipulation in both simulated and real-world environments. • Integrate your work with NVIDIA’s advanced robotics platforms. • Transfer your innovations into products, with deliverables including prototypes, patents, and/or publications in top conferences and journals.
• Collaborate with researchers and engineers on focused projects in humanoid robotics loco-manipulation and mobile manipulation areas. • Support the development and advancement of GR00T and Cosmos foundation models. • Help develop reference workflows with Isaac Lab and Newton for humanoid and mobile manipulation dexterous tasks. • Advanced technologies for robot learning and synthetic data generation using human videos. • Design, implement, and test novel algorithms for humanoid robot locomotion and manipulation in both simulated and real-world environments. • Drive a scoped internship project from model/algorithm design and sim-to-real transfer through to on-robot validation, with the potential for open-source contributions or publications. • Collaborate cross-functionally with teammates and partners to share findings and advance shared goals.
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