Machine Learning Engineer - AI Operations

Experian is a global data and technology company, powering opportunities for people and businesses around the world. We help to redefine lending practices, uncover and prevent fraud, simplify healthcare, create marketing solutions, and gain deeper insights into the automotive market, all using our unique combination of data, analytics and software. We also assist millions of people to accomplish their financial goals and help them save time and money.

We operate across a range of markets, from financial services to healthcare, automotive, agribusiness, insurance, and many more industry segments.

We invest in people and new advanced technologies to unlock the power of data. As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), we have a team of 22,500 people across 32 countries. Our corporate headquarters are in Dublin, Ireland. Learn more at experianplc.com.

We are looking for a experienced and proactive Machine Learning Engineer to join our AI Operations & Safety team at Experian. Reporting into the Senior Management of the team you will contribute to the secure, compliant, and responsible deployment of generative AI (GenAI) models across financial services. You will work with senior engineers, risk and compliance teams, and product stakeholders to ensure AI systems are explainable and aligned with regulatory and ethical standards.

What you'll do:

• Help implement Responsible AI frameworks and governance policies.
• Collaborate with risk, compliance, and legal teams to ensure AI systems meet regulatory expectations.
• Contribute to documentation and audits related to AI safety, fairness, and transparency.
• Maintain tools for genAI model deployment, monitoring, and lifecycle management.
• Implement guardrails for model performance, explainability, and risk mitigation.
• Help with incident response and root cause analysis for AI-related issues.
• Improve ML pipelines for model validation, evaluation, and monitoring.
• Contribute to the development of GenAI-powered solutions in areas such as fraud detection, credit risk, and customer service automation.
• Collaborate with product and engineering teams to integrate AI capabilities into scalable systems.
• Participate in code reviews, design discussions, and sprint planning.

What you'll bring:

• 3–5 years of experience in machine learning, data science, or software engineering.
• Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, and scikit-learn).
• Knowledge of MLOps tools and practices (e.g., MLflow, Kubeflow, and CI/CD for ML).
• Understanding of AI governance, model risk management, and regulatory compliance in financial services will be an advantage.
• University degree in Computer Science, Engineering, Data Science, or a related field.
• Excellent written and verbal English skills.

You will get:

• Personal Development - career pathway for professional growth supported by learning and development programs and unlimited access to online educational training courses, learning materials and books.
• Work environment - excellent work conditions with friendly environment, recognized team spirit, and fun and quality recreation time.
• Social benefit package including life insurance, food vouchers, additional health insurance, monthly flex allowance and internet coverage, corporate discounts, marriage and childbirth / adoption allowance, Multisport card, Sharesave plan, Employee assistance program, а birthday gift and many other benefits!
• Work-life balance - 25 days paid vacation, 1 additional day off for your birthday and extra 3 paid days for participation in Social responsibility event.
• Opportunity for Flexible working hours and Home Office.

Experian is an Equal opportunity employer. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity.

#LI-Hybrid

This is a hybrid remote/in-office role.

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