Senior Solutions Architect, Robotics Foundation Model Training

What you'll do

• Architect and optimize end-to-end training workflows for robotics foundation models; scale training workloads across multi-GPU and multi-node systems.
• Build proof-of-concepts, reference architectures, and agentic workflows for experimentation, benchmarking, and model improvement.
• Find data-pipeline bottlenecks and collaborate with product and engineering teams to inform Physical AI platforms.

What they ask for

• 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; experience across the model lifecycle, including pre-training, fine-tuning, post-training, evaluation, and optimization.
• Expertise in distributed training and multimodal training frameworks; experience with high-throughput data pipelines for large-scale training.

Nice to have

• Familiarity with NVIDIA AI and robotics platforms, or experience with robotics AI workloads and synthetic data generation.
• Experience with profiling tools, improving training efficiency, or building agentic workflows for research acceleration.

Pay

152,000 USD - 241,500 USD (base salary, Level 3); 184,000 USD - 287,500 USD (base salary, Level 4)

Tools

PyTorch, NVIDIA NeMo, JAX, Hugging Face Transformers, Cosmos, GR00T, Isaac Sim, Isaac Lab

AI focus

Training and scaling robotics foundation models, including multimodal models, reinforcement learning, model evaluation, and agentic workflows for experimentation and research acceleration.