Senior Solutions Architect, Robotics Foundation Model Training

🔥 0 minutes ago

🏄 California – Remote

🏄 California – Remote

💵 $152k - $287.5k / year

⏰ Full Time

🟠 Senior

💻 Solutions Engineer

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👻 Ghost score 1%

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Engage with researchers and ML engineers to architect and optimize end-to-end training workflows for robotics foundation models, including World Models, VLAs, and WAMs • Build proof-of-concepts, reference architectures, and agentic workflows to accelerate experimentation, benchmarking, and model improvement of NVIDIA’s robotics open model platforms, including Cosmos and GR00T • Scale pre-training, fine-tuning, and reinforcement learning workloads across multi-GPU and multi-node systems • Improve utilization, throughput, and memory efficiency • Identify and eliminate data pipeline bottlenecks across storage, networking, preprocessing, and data loading for multimodal datasets including video, sensor data, and trajectories • Collaborate with NVIDIA product and engineering teams to provide feedback shaping future Physical AI platforms • Work across research, engineering, and customer teams, influencing product direction and applied AI adoption

🎯 Requirements

• 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, 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, including data/model/pipeline parallelism, sharding, and checkpointing, 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 such as decoding, tokenization, and batching • Strong communication skills with the ability to effectively collaborate across Researchers, Engineers, and executives • Familiarity with NVIDIA AI and robotics platforms such as Cosmos, GR00T, NeMo, Isaac Sim, and Isaac Lab • Experience with robotics AI workloads, including reinforcement learning in simulation and synthetic data generation • Experience profiling and optimizing workloads using Nsight Systems, Nsight Compute, or PyTorch Profiler • Demonstrated impact improving training efficiency and scaling performance • Experience building agentic workflows for automated experimentation, model evaluation, data analysis, or research acceleration

🏖️ Benefits

• Equity • Benefits