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Morela is proud to be supporting our client in recruiting an Ethical & Human Factors SME to ensure AI systems are deployed in a safe, ethical, and human-centred manner. This is a unique opportunity to shape responsible AI adoption in high-stakes operational environments. Contract Details: Duration: 3+ years IR35: Inside Clearance: SC or DV required Day Rate: £700-£900 (depending on experience) Role Overview: You will lead the integration of ethical principles and human factors into AI assurance processes, ensuring that AI adoption considers societal, cultural, and operational impacts alongside technical reliability. Your guidance will influence design, deployment, and governance of AI systems to be trustworthy, transparent, and aligned with emerging regulatory frameworks. Key Responsibilities: Integrate ethical, human factors, and societal considerations into AI assurance processes Develop and implement frameworks for human oversight, trust, accountability, and explainability Conduct ethical risk assessments covering fairness, bias, autonomy, and proportionality of AI decision-making Advise on human-machine interaction, including usability, operator trust, and training requirements Contribute to TEV&V activities with a focus on safety, resilience, and ethical compliance Guide stakeholders on adherence to ethical principles, AI Strategy, and regulatory req

Morela is supporting our client in securing an experienced AI Assurance ML Ops professional to join a high-impact programme. This is a chance to ensure AI/ML systems are safe, auditable, and fully aligned with regulatory and ethical standards in complex operational environments. Contract Details: Duration: 3+ years IR35: Inside Clearance: SC or DV required Day Rate: £700-£900 (depending on experience) Role Overview: In this role, you will integrate assurance into every stage of the AI/ML lifecycle. From data preparation to production deployment, you will embed governance, risk management, and monitoring practices to make AI systems reliable, transparent, and compliant. Key Responsibilities: Establish and maintain assurance processes within ML Ops pipelines Apply governance and risk frameworks throughout model development and deployment Implement and lead monitoring practices for bias, data drift, model drift, explainability, and system robustness Provide guidance on TEV&V practices for models under development or in production Partner with Data Science, Risk, and Compliance teams to align AI systems with organisational, ethical, and regulatory requirements Required Expertise: Extensive ML Ops / ML Engineering exp