Principal Architect, AI Factory (Physical AI)

What you'll do

• Define the data architecture for Physical AI and autonomous systems to enable learning and reasoning at scale.
• Establish canonical data models and architectural standards to transform raw sensor and telemetry data into reusable assets.
• Design technical infrastructure including specific databases, programming languages, utilities, and testing approaches.
• Lead the evaluation and deployment of new technologies to enhance existing digital technical capabilities.
• Develop detailed architecture deliverables and IT blueprints to solve complex business problems.
• Create scalable data products for training, fine-tuning, and validating next-generation AI models.
• Translate architecture into implementation plans and reference standards across various platform teams.
• Manage the end-to-end MLOps lifecycle including model registry, deployment, monitoring, and governance.

What we're looking for

• Bachelor’s degree in Computer Science, Computer Engineering, or a related field.
• Master’s or doctoral degree (preferred).
• 8+ years of experience architecting distributed AI infrastructure on-premises and in the cloud (preferred).
• Proficiency in Python and working knowledge of C++.
• Expertise in data architecture, platform architecture, and requirements analysis.
• Experience with Kubernetes, Slurm, Terraform, Ansible, and Helm (preferred).
• Experience with PyTorch, TensorRT, DeepSpeed, and MLflow (preferred).
• Experience with NVIDIA ecosystems, including DGX, CUDA, and Triton (preferred).