Teams at Graphcore

Develop and optimize state-of-the-art machine learning models for specialized AI hardware and systems containing thousands of accelerators. Responsibilities include model training, benchmarking, profiling, kernel optimization, experimentation, software testing, code reviews, and collaboration with research, software, and product teams. The role focuses on performance, scalability, distributed training and inference, and advancing next-generation AI hardware and software.

Investigate a next-generation AI computing architecture across rack and data-centre scales. Design experiments, benchmark AI workloads, analyse hardware-software interactions, and evaluate system performance, scalability, and reliability. Develop automation and tooling to collect, analyse, and visualise system metrics, communicating findings with clear, reproducible evidence while collaborating across engineering teams.

Develop internal tooling and technical processes for building, testing, integrating, and releasing Graphcore’s machine learning software stack. Guide developers on build practices and dependency management, collaborate with QA and software teams to resolve integration issues, contribute software fixes, and help ensure reproducible builds in secure, sandboxed environments.