Senior ML Engineer – AI Safety

Develop explainability and interpretability tooling to support model audits, regulatory reviews, and clear communication of model behaviour and limitations.

Partner with risk, compliance, legal, privacy, security, product, and engineering teams to embed safety requirements into scalable GenAI solutions.

Lead incident response and root cause analysis for AI-related safety issues, including post-incident reviews and remediation playbooks.

Contribute to GenAI-powered solutions in fraud detection, credit risk, customer service automation, and platform initiatives while ensuring alignment with AI risk appetite.

Mentor junior and mid-level engineers and represent AI Safety in cross-functional forums.

Required qualifications

Experience in machine learning, data science, or software engineering, including focused on AI safety, alignment, Responsible AI, or model governance.

Strong Python skills and proficiency with ML frameworks such as TensorFlow, PyTorch, scikit-learn, or equivalent tooling.

Hands-on MLOps experience, including MLflow, Kubeflow, CI/CD for ML, model monitoring, versioning, and reproducible deployment practices.

Demonstrated knowledge of AI safety techniques including red-teaming, adversarial testing, fairness metrics, interpretability methods, and alignment approaches.

Strong understanding of AI governance, model risk management, and regulatory expectations in financial services, with practical experience preparing documentation for audit or regulatory review preferred.

Excellent written and verbal English skills, with the ability to translate complex safety concepts for non-technical audiences.

Nice-to-have

Experience designing or running automated benchmark suites for LLMs or other GenAI systems.

Familiarity with bias detection, harm classification, content safety tooling, or policy evaluation frameworks.

Experience with regulated financial services use cases such as fraud detection, credit risk, customer service automation, or model risk management.

Experience influencing engineering standards or mentoring engineers in AI safety, Responsible AI, or production ML practices.

At Serasa Experian, we believe that diversity is essential for a healthier and more innovative work environment, where everyone can share experiences and express their ideas. That’s why we promote several initiatives to support inclusive recruitment and the professional development of our people.

We also have our affinity groups, created to empower and support individuals from underrepresented groups: ExperianPride (LGBTQIAPN+ community), Ubuntu (racial equity), Women in Experian (gender equity), Aspire (people with disabilities), and Connecting Generations (generations).

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