<p>The AI Model Evaluator role focuses on validating, testing and auditing machine learning models to ensure accuracy, fairness and compliance. The evaluator collaborates closely with data scientists, engineers and product teams to translate business requirements into robust evaluation criteria.</p>
<h2>AI Model Evaluator Job Profile</h2>
<p>The AI Model Evaluator provides an independent assessment of model performance across the model lifecycle. This includes designing evaluation protocols, running experiments, and documenting findings in a way that is actionable for model owners.</p>
<p>Working within cross-functional teams, the evaluator identifies sources of bias, verifies data provenance, and ensures models satisfy regulatory and organisational standards. Effective communication of technical results to non-technical stakeholders is essential.</p>
<h2>AI Model Evaluator Job Description</h2>
<p>The AI Model Evaluator will plan and execute evaluation strategies for supervised and unsupervised models, including classification, regression, clustering and generative models. You will devise benchmarks, select appropriate metrics and run reproducible tests that reflect real-world usage and edge cases.</p>
<p>Key duties include constructing test datasets that represent diverse populations, analysing model behaviour under distributional shifts and stress testing to reveal failure modes. You will collaborate with data engineers to ensure data quality and with compliance teams to align evaluation work with legal and ethical frameworks.</p>
<p>The role demands a pragmatic blend of domain knowledge and technical rigour. You will produce clear, evidence-based reports and recommendations, suggest remediation techniques such as recalibration, reweighting or retraining, and contribute to the development of evaluation tooling and automation.</p>
<h2>AI Model Evaluator Duties and Responsibilities</h2>
<ul>
<li>Design and implement comprehensive evaluation plans for ML models and pipelines</li>
<li>Define and track key performance metrics, including accuracy, F1, AUC, calibration and fairness measures</li>
<li>Create representative test datasets and synthetic scenarios for stress testing</li>
<li>Conduct bias and fairness analyses across sensitive attributes and subgroups</li>
<li>Perform error analysis to uncover root causes and recommend mitigations</li>
<li>Automate evaluation workflows and maintain reproducible evaluation artefacts</li>
<li>Collaborate with model developers to validate fixes and ensure robust deployment</li>
<li>Support model governance by documenting evaluations, assumptions and limitations</li>
<li>Engage with legal and compliance teams to ensure regulatory alignment</li>
<li>Present findings to technical and non-technical stakeholders in a clear manner</li>
</ul>
<h2>AI Model Evaluator Requirements and Qualifications</h2>
<ul>
<li>Bachelor's or Master’s degree in Computer Science, Statistics, Mathematics or a related discipline</li>
<li>Proven experience evaluating machine learning models in production or research settings</li>
<li>Strong understanding of statistical methods, hypothesis testing and experimental design</li>
<li>Proficiency in Python and familiarity with libraries such as scikit learn, TensorFlow or PyTorch</li>
<li>Experience with data handling, labelling practices and constructing validation datasets</li>
<li>Knowledge of fairness, accountability and transparency principles in AI</li>
<li>Familiarity with model monitoring, A/B testing and deployment considerations</li>
<li>Excellent analytical, written and verbal communication skills</li>
<li>Ability to work collaboratively in cross-functional teams and present complex findings to senior stakeholders</li>
<li>Preferred: experience with model explainability tools and MLOps platforms</li>
</ul>