Systems Performance Engineer, AI Infrastructure

📋 Job Overview

CommonAI CIC is seeking a Performance Engineer to design and run experiments that reveal how AI infrastructure behaves, what limits its performance and how reliably that behaviour can be predicted. You will build measurement tools and turn observations of real hardware and software into evidence for SIL’s simulation platform and the investment decisions it supports.

🏢 About CommonAI

CommonAI CIC is a non-profit organisation built around collaborative engineering and is backed by a mix of UK Government and private funding in order to design, build and deploy innovative AI systems. Our Scaling Inference Lab (SIL) is developing simulation grounded in real measurements to help the UK invest in promising AI infrastructure.

🎯 The Role

You will design and run experiments that reveal how AI infrastructure behaves, what limits its performance and how reliably that behaviour can be predicted. Your work will range from targeted experiments on individual components to measurements of complete LLM serving systems. Working with workload, simulation and uncertainty specialists, you will investigate bottlenecks, explain performance variation and identify the meaningful effects.

✅ Key Responsibilities

• Design and run reproducible experiments, from individual hardware or software components to complete LLM serving systems, covering relevant workloads, configurations and operating conditions.
• Develop reusable measurement tools and collect traces, profiles and counters to characterise latency, throughput, memory behaviour and, where reliable measurement is possible, power and energy.
• Investigate bottlenecks, performance variation and unexpected behaviour across the layers your expertise covers, working with colleagues to extend the investigation through the stack.
• Take responsibility for reproducible workload details, software versions, configuration and measurement methods so results can be reproduced, compared and used to calibrate simulator models.
• Work with simulation and uncertainty specialists to choose measurements that resolve important unknowns and undertake curation of calibration and validation data.
• Help define the controls needed for experiments and use the resulting cluster-control interfaces, coordinating access and changes with colleagues responsible for the hardware.

📌 Required Qualifications

• Experience investigating the performance of real computing systems and designing experiments that support rigorous conclusions.
• Depth in one or more relevant areas: accelerator profiling, inference runtimes, memory systems, distributed/HPC workloads, networking, or power and energy measurement.
• The ability to build maintainable automation and analysis tools in a suitable software language, and to learn unfamiliar profiling tools.
• Knowledge and care of experimental controls, repeatability, confounding effects and the limits of a measurement.
• Some experience using AI coding agents, alongside sound debugging and review habits.

⭐ Desirable Experience

• LLM serving experience and familiarity with tools such as Nsight, PyTorch Profiler or system/network profilers.

🎁 Benefits

• A collaborative and supportive work environment
• The opportunity to have a high impact in a growing organisation
• Competitive salary package, including pension and benefits
• Professional development opportunities
• Networking opportunities with influential figures from across the tech sector and academia
• A vibrant office environment located a few minutes’ walk away from Cambridge train station

🛂 Visa & Eligibility

Applicants across the UK are welcome. We are open to permanent employment, part-time arrangements and consultancy.