CommonAI CIC is a non-profit organisation focused on collaborative engineering and innovative AI systems. The Scaling Inference Lab (SIL) is developing simulation to help the UK invest in promising AI infrastructure. This role involves helping investors turn questions about AI infrastructure into technical evidence they can use, translating between investment and engineering audiences.
🏢 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. We connect proposed hardware designs to realistic workloads, helping investors and engineers understand their potential, their limitations and the next experiment worth doing.
🎯 The Role
Help investors turn questions about AI infrastructure into technical evidence they can use. You will translate between investment and engineering audiences, turning diligence questions into well-defined simulation studies and experiments, and explaining what the findings mean for a proposed technology. Working with the engineering team, you will make SIL's simulation framework accessible to investors without specialist systems knowledge. You will guide users through studies, help them understand the assumptions and uncertainty behind the results, and turn their feedback into improvements to our framework.
✅ Key Responsibilities
Work with investors to understand an investment or diligence question, alternatives being considered and the evidence needed to move it forward.
Turn those questions into clear study briefs with the simulation team, including assumptions, relevant workloads and criteria for a useful result.
Help investors use the framework through guided studies and clear explanations, and translate their feedback into proposed improvements for the engineering team.
Produce concise assessments explaining technical findings, assumptions, uncertainty, integration requirements and the next evidence worth obtaining.
Bring together simulator results, company and research developments, and investor questions to contribute to the Scientific Director's technology roadmap for SIL.
📌 Required Qualifications
The ability to understand complex technology, connect technical findings to investment questions, and explain their implications clearly to engineering and investment audiences.
Relevant experience in technical analysis, technology diligence, deep-tech commercialisation, engineering with customer or investor engagement, or a comparable field.
Sound quantitative judgement and the curiosity to test assumptions and assess the evidence behind performance or cost claims.
Strong listening, relationship-building and writing skills, including the ability to make uncertainty understandable and earn trust with different audiences.
⭐ Desirable Experience
Familiarity with AI infrastructure, semiconductors, HPC or the economics of deploying technology.
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