governing AI applications in the energy sector and the clients opportunity to influence their development. Interpret and apply relevant regulations, including the EU General Data Protection Regulation (GDPR), EU Act and adhere to the five principles outlined by the AI Office in the UK. Apply expertise in AI ethics … develop and implement a comprehensive framework for ethical AI use within the organisation. Collaborate with stakeholders, including colleagues in the legal and regulatory teams, datascience and analytics, technology, developers and business leaders to integrate compliance considerations into existing processes and workflows and the AI development lifecycle. Engage … ethics, ensuring timely delivery and alignment with business objectives. Required Skills and Experience: Bachelor's degree in a relevant field such as ethics, computer science, or business; advanced degree preferred. Proven experience in AI ethics, with a deep understanding of ethical principles, regulatory requirements, and best practices. Familiarity with more »
secure operation of AI and ML systems. Responsibilities: Develop and own robust enterprise security architecture for AI/ML systems, CI/CD and data pipelines. Participate in enterprise-wide architecture initiatives for AI/ML. Understand the workflow and pipeline architectures of ML and deep learning workloads. Conduct … ML models, LLM and development of trustworthiness, safety, fairness, bias and inappropriateness detection, as well as adversarial test specification, development, and execution. Collaborate with data scientists, engineers, and other stakeholders to embed security controls and measures into AI/ML applications, models, algorithms, and data pipelines. Define and … enforce robust access controls, authentication mechanisms, and encryption standards to safeguard AI/ML systems, training data, provenance, and any sensitive data. Stay abreast of emerging AI security threats, trends, and technologies, evaluating their impact and proactively adapting security measures to mitigate potential risks. Provide technical guidance and support more »
secure operation of AI and ML systems. Responsibilities: Develop and own robust enterprise security architecture for AI/ML systems, CI/CD and data pipelines. Participate in enterprise-wide architecture initiatives for AI/ML. Understand the workflow and pipeline architectures of ML and deep learning workloads. Conduct … adversarial test specification, development, and execution. Define and enforce robust access controls, authentication mechanisms, and encryption standards to safeguard AI/ML systems, training data, provenance, and any sensitive data. Stay abreast of emerging AI security threats, trends, and technologies, evaluating their impact and proactively adapting security measures to … security tools, technologies, and frameworks to enhance the overall security posture of AI/ML and other business systems. Develop and maintain relationships between data scientists, data engineers, developers, operations (DevOps, DataOps, MLOps) and business unit leaders to govern and support scalability of the ML and AI initiatives. more »
