Teams at Graphcore

Coordinates engineering planning, schedules, milestones, dependencies, risks, issues, and delivery commitments across multiple teams. Facilitates meetings, maintains dashboards and documentation, supports resource planning, tracks actions, prepares stakeholder reporting, and improves engineering processes. The role works across geographically distributed teams and influences progress without direct authority.

Leads performance optimization for large-scale AI training and inference workloads across distributed systems. Builds benchmarks, profiles workloads, identifies compute, memory, networking, and software bottlenecks, and develops C++ and Python tools. Coordinates complex performance improvements across hardware and software teams, validates results with reliable data, and guides engineering decisions that improve efficiency, scalability, and reliability at data center scale.

Leads the operating model and new-product-introduction framework for AI data center technologies. Defines deployment, service, diagnostics, telemetry, readiness, and lifecycle workflows across compute, networking, storage, power, cooling, and site operations. Coordinates multidisciplinary teams, conducts operational readiness reviews, establishes quality metrics, resolves complex platform issues, guides automation, and communicates risks and recommendations to engineering and operations leaders.