Infrastructure Engineer

Peripheral is developing spatial intelligence technology for live sports, entertainment, robotics, and embodied intelligence. The Infrastructure Engineer will architect and operate cloud infrastructure for large-scale machine learning training, production model serving, data pipelines, and reliable customer-facing systems during live events. The role also includes establishing infrastructure standards, collaborating across research and engineering, and mentoring team members.

Responsibilities:

• Design, build, and operate cloud infrastructure for large-scale ML training, including GPU/TPU compute, job orchestration, and experiment tracking
• Partner with research to scale foundation model training workflows, including distributed PyTorch training and efficient multi-view video data loading
• Build and operate production infrastructure for model deployment and serving, with a focus on reliability, latency, scalability, and cost
• Design reliable data pipelines for moving multi-view video, LiDAR, and other sensor data from capture through customer-facing outputs
• Work across research and engineering to translate infrastructure needs into scalable, self-serve systems and developer tooling
• Establish standards for infrastructure-as-code, CI/CD, monitoring, observability, security, and cloud operations
• Improve the reliability and resilience of customer-facing systems during live, time-sensitive workloads
• Mentor engineers and interns as the infrastructure function grows