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.
Your work will also contribute to the Scientific Director's technology roadmap, bringing together developments in hardware and software, findings from simulation and measurement, and the questions investors need answered next.
- 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.
An example early project would be to work with an investor and the engineering team to compare two AI infrastructure options, producing a concise assessment of the findings, assumptions and further evidence needed to inform an investment decision.