Senior Solutions Architect, Robotics Foundation Model Training
NVIDIA· Architect, Solutions
Santa Clara, CA, Hybrid (CA, Remote)$152k - $241.5kFull-timePosted 1mo ago
About the role
Hands-on Applied Engineer to scale robotics foundation model training, collaborating with researchers, engineers, and customers to move robotics models from experimentation to production across multi-GPU/multi-node setups.
Responsibilities
- Engage with Researchers and ML engineers to architect and optimize end-to-end training workflows for robotics foundation models, like World Models, VLAs, WAMs.
- Build proof-of-concepts, reference architectures, and agentic workflows that accelerate experimentation, benchmarking, and model improvement of NVIDIA’s Robotics Open model platforms like Cosmos and GR00T.
- Scale pre-training, fine-tuning, and reinforcement learning workloads across multi-GPU and multi-node systems, improving utilization, throughput, and memory efficiency.
- Identify and eliminate data pipeline bottlenecks across storage, networking, preprocessing, and data loading for multimodal datasets (video, sensor data, trajectories).
- Collaborate with NVIDIA product and engineering teams to provide feedback that shapes future Physical AI platforms
Qualifications
- MS, PhD, or equivalent experience in Computer Science, Artificial Intelligence, Electrical or Computer Engineering, Robotics, or a related field.
- 5+ years of industry or research experience in deep learning, distributed computing, or large-scale model training.
- Hands-on experience training or optimizing multimodal or foundation models (e.g., VLMs, VLAs, World Models), ideally in robotics settings.
- Experience across the AI model lifecycle, including pre-training, supervised fine-tuning, RL or other post-training methods, evaluation, and model optimization.
- Strong expertise in distributed training techniques (data/model/pipeline parallelism, sharding, check-pointing) on multi-GPU or multi-node systems.
- Expertise with multimodal training frameworks such as PyTorch, NVIDIA NeMo, JAX, or Hugging Face Transformers.
- Experience building or working with high-throughput data pipelines for large-scale training, including storage bandwidth, network throughput, and preprocessing (e.g., decoding, tokenization, batching)
- Strong communication skills with the ability to effectively collaborate across Researchers, Engineers and executives.
Skills
Required:Foundation model trainingDistributed trainingMultimodal data pipelinesPyTorch / NeMo / JAX / Hugging FaceCommunication
Benefits
- equity
- benefits (see NVIDIA benefits page)
Last updated Aug 28, 2026. Interested? Apply on the company site.
About NVIDIA
World Leader in AI Computing
NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.
AIautonomous vehiclesgaminggpugraphics cardhigh performance computingliquid-ai-recruiting-targetllm
More open roles at NVIDIA
- Senior Physical Verification Engineer3d agoEngineer, ASIC
- Senior System Software Engineer, Display Security3d agoEngineer, Sys SW
- Senior FPGA Prototyping Engineer - Hardware3d agoSanta Clara, CA · Engineer, ASIC
- Senior Product Engineer3d agoHybrid (Thailand) · Engineer, Product Development
- Senior Architect - Data Processing Systems, Analytics and Data Intelligence3d agoHybrid (Remote / Local) · Architect