Lei Ye is an Infrastructure Architect focused on building production ML systems that are reliable, measurable, and economically scalable. She works with early-stage AI/ML startups to design the minimum infrastructure needed to ship safely—then iterates toward performance, cost control, and operational clarity as usage grows.

Her work sits at the intersection of platform engineering, MLOps, and systems design: model serving and inference pipelines, data/feature reliability, observability, incident readiness, and cost-performance trade-offs across compute, storage, and orchestration.

Lei’s approach is “pair-design”: she produces clear architecture decisions, implementation plans, and measurable milestones, while reducing operational risk through tight scopes, review-first changes, and explicit handoff artifacts. she publishes decision logs, diagrams, and reusable modules to make infrastructure work auditable, repeatable, and easier for teams to maintain.