Senior Solutions Architect, Physical AI Cloud

What you'll do

• Help partners build scalable Physical AI pipelines and data factories, including ingestion, synthetic data generation, training, simulation, and evaluation.
• Translate robotics workload needs into optimized cloud-native architectures across hybrid infrastructure.
• Accelerate distributed inference and provide technical guidance to customers and internal teams.

What they ask for

• Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
• 5+ years in Solution Architecture or Infrastructure Engineering, advancing AI/ML systems from proof of concept to production on private or public cloud.
• Experience scaling Robotics workloads in one or more listed areas, and hands-on experience operating Kubernetes platforms for distributed GPU and AI workloads.
• Expertise in networking, storage, workflow orchestration, DevOps practices, GPU workload orchestration, and strong communication skills.

Nice to have

• Hands-on robotics framework or NVIDIA platform experience, such as ROS2, Isaac Lab, Isaac Sim, GR00T, or Cosmos.
• Experience with large-scale robotics data pipelines, NVIDIA inference technologies, agentic workflows, or APIs such as REST and gRPC.

Pay

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

Tools

Kubernetes, OSMO, NIM, TensorRT-LLM, vLLM, SGLang, Airflow, Argo

AI focus

Supports Physical AI workloads: robotics simulation, synthetic data generation, multimodal model training, robot learning, and distributed inference; also mentions AI models for data labeling and agentic workflows.