About this role
Salary: £45,000 - 80,000 per year
Requirements: Background in distributed HPC, cloud environments, data engineering and analytics.Knowledge of EDA workflows and semiconductor engineering environments.Proficiency in Python and data analysis or ML frameworks.Ability to turn sophisticated data into clear, actionable strategy.Experience with IBM Spectrum LSF or other job schedulers is a plus.Familiarity with NetApp or high-performance storage systems is a plus.Experience applying AI or ML to workload optimization or resource management is a plus.Experience building production-grade data pipelines is a plus.Exposure to FPGA and Emulation infrastructure is a plus. Responsibilities: Contribute to improvements in HPC scheduling and infrastructure efficiency.Assist with performance benchmarking activities to support platform decisions.Develop dashboards and visualisations.Analyse Cost and Usage Reports (CUR) and infrastructure metrics to support forecasting, budgeting, and optimisation strategies for large-scale compute environments.Build and maintain scalable analytics frameworks to measure utilisation, capacity, and workload behaviour.Partner with engineering, operations, and finance teams to ensure data-driven decision making. Technologies: AICloudFPGAIBMIBM SpectrumSupportPythonARMC++ More:
We are looking for an EDA Optimisation Engineer to support the data-driven optimisation, analysis and maintenance of our engineering platforms. This role sits within our Productivity Engineering group and focuses on metrics, automation, data engineering, and problem-solving in a metrics-first, data-driven environment. We work across HPC compute, cloud, Emulation and FPGA environments to improve system utilisation, efficiency, cost-performance, forecasting accuracy, and infrastructure strategy. We offer a collaborative, fast-paced team where you can grow technically, contribute directly to platform strategy, and improve performance for thousands of engineers. No relocation package is available for this role. We also support hybrid working, with patterns determined by the teams needs, and we are an equal opportunity employer committed to mutual respect and inclusion.
last updated 40 week of 2026