Uncertainty-Driven AI Simulator Engineer

CommonAI C.I.C.; Town of Cambridge; Hybride; AUD 144 000 - 211 000; Plein temps

Avantages offerts par ce poste

Vibrant Cambridge office

Hybrid work model

Competitive salary + pension

Résumé du poste

CommonAI CIC in Cambridge is seeking a researcher to develop methods for calibrating AI simulators and quantifying uncertainty in design comparisons. You will combine mathematical reasoning with software engineering to calibrate models against measurements and test predictions on independent cases.

The role welcomes applicants from AI systems, HPC and related fields. You will work with measurement and workload engineers to design experiments, integrate uncertainty outputs into repeatable

Qualifications

• Mathematical maturity: ability to reason about models, data, variation and the assumptions behind a quantitative claim.
• Software engineering experience to turn numerical methods into readable, tested, reusable tools.
• Experience in one or more: quantitative systems performance analysis, statistical modelling, simulation validation, uncertainty quantification, scientific/HPC software or the theory of experimental design.
• Ability to collaborate with specialists and explain results and limits of evidence.

Responsabilités

• Develop and implement methods to calibrate simulator models against measurements and evaluate predictions on unseen cases.
• Distinguish uncertainty from measurements, model assumptions, parameters, and variation; represent it appropriately.
• Analyse sensitivity and uncertainty in comparisons between alternatives and their shared uncertainty sources.
• Develop outputs showing prediction uncertainty, ranking stability, and evidence limits.

Connaissances

Mathematical maturity

Software engineering

Uncertainty quantification

Bayesian methods

Experimental design

Description du poste

CommonAI CIC in Cambridge is seeking a researcher to develop methods for calibrating AI simulators and quantifying uncertainty in design comparisons. You will combine mathematical reasoning with software engineering to calibrate models against measurements and test predictions on independent cases.

The role welcomes applicants from AI systems, HPC and related fields. You will work with measurement and workload engineers to design experiments, integrate uncertainty outputs into repeatable