Senior Principal Architect, ML Infrastructure

15+ years of meaningful software engineering experience, including significant architecture-level ownership in ML, data infrastructure, or high-scale systems Proven experience leading the design of ML platforms that serve large-scale training and inference workloads Deep technical fluency in distributed storage, high-volume data pipelines, and data compression strategies for ML use cases Strong knowledge of Linux systems, Python, and C++ or similar performance-oriented languages Experience operating in hybrid environments: bare metal, HPC, and public cloud (AWS/GCP/Azure) Comfortable owning cross-org initiatives and influencing system-level design Prior work in robotics, autonomous vehicles, or safety-critical domains strongly preferred

Own the architecture of ML data infrastructure Design and evolve infrastructure for petabyte-scale ML workflows Architect high-throughput systems for distributed training on large GPU clusters Establish robust data governance, observability, and retention strategies Collaborate cross-functionally with ML engineers, researchers, data engineers, and DevOps Lead technical strategy and roadmap development for the ML & Data Platform team Mentor and influence engineers across teams