高级机器学习工程师 – 人工智能安全
Senior ML Engineer – AI Safety
#### 公司简介
Experian 是一家全球性的数据和技术公司，为世界各地的个人和企业创造机会。我们运营的市场包括金融服务、医疗保健、汽车、农业、保险等。Experian 投资于人才和先进的新技术，以释放数据的潜力。我们在 32 个国家拥有 25,200 名员工。
我们的独特之处在于重视您的价值。Experian 的以人为本、包容性和目标驱动的文化获得了众多奖项的认可——包括 2025 年世界最佳工作场所™（财富全球前 25 强）以及在 26 个国家获得的“最佳工作场所™”等。请关注 Experian 的社交媒体或浏览我们的职业网站，了解原因。Experian 还自豪地成为平等机会雇主和积极行动雇主。如果您有残疾或需要特殊安排，请尽快告知我们。
#### 职位描述
我们正在寻找一位经验丰富的高级机器学习工程师加入 Experian 的 AI 安全团队。您将负责在业务范围内设计、实施和管理安全关键型 GenAI 系统，与高级工程师、安全、风险、合规、法律和产品利益相关者合作，确保 AI 系统具备稳健性、可解释性、公平性、可审计性，并符合监管和伦理标准。作为高级贡献者，您将指导工程师，制定技术战略，并帮助推动组织内 AI 安全最佳实践的采用。
**主要职责**
- 领导负责任 AI 框架、治理政策和安全防护机制的设计与实现，用于 GenAI 系统。
- 定义并负责 AI 安全评估流程，包括红队测试、对抗鲁棒性测试、越狱和提示注入评估，以及自动化安全基准测试。
- 开发可解释性和可理解性工具，以支持模型审计、监管审查以及清晰传达模型行为和限制。
- 与风险、合规、法律、隐私、安全、产品和工程团队合作，将安全需求嵌入可扩展的 GenAI 解决方案中。
- 领导 AI 相关安全问题的事件响应和根本原因分析，包括事后审查和补救计划。
- 为欺诈检测、信用风险、客户服务自动化和平台项目等 GenAI 驱动的解决方案做出贡献，同时确保与公司目标一致
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#### Company Description
Experian 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.
#### Job Description
We 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 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.
#### Qualifications
**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.
#### Additional Information
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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