NVIDIA accelerates humanoid robots’ development with the Isaac solution and GR00T blueprint. We’re now looking for a robotics expert, especially in Foundation Model to support this effort. As a Solutions Architect, you’ll collaborate with an exceptional and highly collaborative research team known for influential work in multimodal foundation models, large-scale robot learning, embodied AI, and physics simulation, pushing the frontier of humanoid robotics. What you will be doing: + Design, implement, and optimize scalable ML training pipelines for training multimodal foundation models for robotics. + Collaborate with researchers to integrate cutting-edge model architectures into scalable training pipelines. + Implement scalable data loaders and preprocessors for multimodal datasets, such as videos, text, and sensor data. + Optimize GPU and cluster utilization for efficient model training and fine-tuning on massive datasets. + Develop robust monitoring and debugging tools to ensure the reliability and performance of training workflows on large GPU clusters. What we need to see: + Bachelor's degree in Computer Science, Robotics, Engineering, or a related field. + 3+ years of full-time industry experience in large-scale MLOps and AI infrastructure. + Proven experience designing and optimizing distributed training systems with frameworks like PyTorch, JAX, or TensorFlow. + Deep understanding of GPU acceleration, CUDA programming, and cluster management tools like Kubernetes. + Strong programming skills in Python and a high-performance language such as C++ for efficient system development. + Strong experience with large-scale GPU clusters, HPC environments, and job scheduling/orchestration tools (e.g., SLURM, Kubernetes). Ways to stand out from the crowd: + Master’s or PhD’s degree in Computer Science, Robotics, Engineering, or a related field. + Demonstrated Tech Lead experience, coordinating a team of engineers and driving projects from conception to deployment. + Strong experience at building large-scale LLM and multimodal LLM training infrastructure.