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Senior ML Engineer - AI Safety

Experian · Flexible / Remote

Publicada em 02/10/2026

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Company DescriptionExperian is a global data and technology company that drives opportunities for people and businesses around the world. We operate in diverse markets such as financial services, healthcare, automotive, agribusiness, insurance, and more. Experian invests in people and advanced new technologies to unlock the power of data. We have an incredible team of 25,200 employees in 32 countries.Our uniqueness is valuing yours. Experian's people-centric, inclusive, and purpose-driven culture is recognized by numerous awards - including World's Best Workplaces™ 2025 (Fortune's Top 25 global) and Great Place To Work™ in 26 countries, among others. Check out Experian Life on social media or explore our careers website to understand why. Experian is also proud to be an equal opportunity employer and an affirmative action employer. If you have a disability or need that requires accommodation, please let us know as soon as possible. DescriptionWe are looking for an experienced, proactive Senior ML Engineer to join Experian's AI Safety team. You will lead the design, implementation, and governance of safety-critical GenAI systems across the business, partnering with senior engineers, security, risk, compliance, legal, and product stakeholders to ensure AI systems are robust, explainable, fair, auditable, and aligned with regulatory and ethical standards. As a senior contributor, you will mentor engineers, shape technical strategy, and help drive adoption of AI safety best practices across the organisation. Key responsibilities Lead the design and implementation of Responsible AI frameworks, governance policies, and safety guardrails for GenAI systems.Define and own AI safety evaluation pipelines, including red-teaming, adversarial robustness testing, jailbreak and prompt injection assessments, and automated safety benchmarks.Develop explainability and interpretability tooling to support model audits, regulatory reviews, and clear communication of model behaviour and l
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