2,359 Ethical AI jobs in the United Kingdom

• Conduct cutting-edge research on AI ethics, bias, fairness, transparency, and accountability.
• Develop and implement frameworks, policies, and best practices for responsible AI development and deployment.
• Collaborate closely with AI/ML engineers, data scientists, and product managers to integrate ethical considerations into system design and implementation.
• Perform ethical risk assessments for new and existing AI systems.
• Advise on regulatory compliance and industry standards related to AI ethics.
• Contribute to public discourse and thought leadership on AI ethics through publications, presentations, and workshops.
• Develop training materials and conduct workshops for internal teams on AI ethics principles.
• Monitor evolving societal and technological trends to anticipate future ethical challenges in AI.
• Engage with external stakeholders, including academics, policymakers, and civil society organisations.

• Advanced degree (PhD preferred) in Computer Science, Philosophy, Law, Social Sciences, or a related field with a specialization in AI ethics or responsible AI.
• Demonstrated experience in conducting research and publishing in the field of AI ethics.
• Strong understanding of AI/ML technologies and their societal implications.
• Excellent analytical, critical thinking, and problem-solving skills.
• Proven ability to translate complex ethical concepts into actionable guidelines.
• Exceptional written and verbal communication skills.
• Experience in policy development or ethical review processes is a plus.
• Ability to work effectively in a multidisciplinary and fast-paced research environment.

• Developing and evolving our organization's AI ethics principles and guidelines.
• Conducting ethical risk assessments for new and existing AI products and features.
• Designing and overseeing processes for bias detection and mitigation in AI models.
• Creating frameworks for AI transparency, explainability, and accountability.
• Collaborating with legal and policy teams to ensure compliance with emerging AI regulations.
• Developing training materials and delivering workshops on AI ethics for internal teams.
• Advising product and engineering teams on ethical implications of AI design choices.
• Representing the company in external forums and discussions on AI ethics.
• Conducting research on the societal impact of AI technologies.
• Championing a culture of responsible innovation across the organization.

• Developing and implementing comprehensive AI ethics principles, policies, and governance frameworks.
• Conducting thorough ethical impact assessments for new AI products and features.
• Advising product and engineering teams on ethical considerations in AI design, development, and deployment.
• Researching emerging ethical challenges and best practices in AI and machine learning.
• Fostering a culture of responsible AI development within the organization through training and awareness programs.
• Collaborating with external stakeholders, including researchers, policymakers, and industry bodies, on AI ethics initiatives.
• Interpreting and applying relevant regulations and standards related to AI and data privacy.
• Communicating complex ethical issues to diverse audiences, including technical and non-technical stakeholders.
• Contributing to the company's thought leadership in the field of responsible AI.

• Develop and maintain a comprehensive AI ethics framework, guidelines, and best practices.
• Conduct ethical risk assessments and impact analyses for new and existing AI projects.
• Collaborate with AI researchers, engineers, product managers, and legal counsel to integrate ethical considerations throughout the AI lifecycle.
• Provide expert guidance on issues such as bias detection and mitigation, fairness, transparency, accountability, and privacy in AI systems.
• Stay abreast of global AI regulations, standards, and evolving ethical discourse.
• Develop and deliver training programs on AI ethics for internal stakeholders.
• Champion a culture of responsible AI innovation across the organization.
• Engage with external stakeholders, academics, and policymakers to contribute to the broader AI ethics community.
• Design and implement mechanisms for ongoing monitoring and auditing of AI systems for ethical compliance.
• Serve as a trusted advisor to senior leadership on all AI ethics-related matters.

• Master's or PhD in a relevant field such as Ethics, Philosophy, Law, Computer Science, Data Science, or a related discipline with a focus on AI ethics.
• Minimum of 5-7 years of experience in AI ethics, responsible AI, or a related field.
• Demonstrated understanding of AI technologies, machine learning principles, and their societal implications.
• In-depth knowledge of ethical theories, frameworks, and best practices in technology.
• Experience in conducting ethical impact assessments and developing mitigation strategies.
• Excellent analytical, critical thinking, and problem-solving skills.
• Strong communication and interpersonal skills, with the ability to articulate complex ethical concepts to diverse audiences.
• Proven ability to influence and drive change within an organization.
• Experience in developing and delivering training materials.
• Familiarity with relevant global regulations and policy discussions around AI.

• Deliver engaging lectures and tutorials in AI, Machine Learning, and related subjects.
• Develop and update course content to reflect the latest advancements in the field.
• Supervise undergraduate and postgraduate student research projects and dissertations.
• Conduct original research, leading to publications in high-impact journals and conferences.
• Actively seek and secure external research funding from various sources.
• Collaborate with faculty on interdisciplinary research initiatives.
• Mentor junior researchers and contribute to the academic development of the department.
• Contribute to the administrative and strategic planning of the department.
• Engage in outreach activities to promote AI and ML education and research.

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field.
• A strong record of peer-reviewed publications in leading AI/ML venues.
• Demonstrated experience in university-level teaching and curriculum development.
• Proven ability to secure research grants.
• Excellent command of AI and Machine Learning concepts and methodologies.
• Strong analytical and problem-solving skills.
• Exceptional communication, presentation, and interpersonal abilities.
• Experience in supervising graduate students.

Job Title: Machine Learning Engineer

Location: London, UK (Hybrid – 2–3 days onsite per week)

Contract Type: Contract

Duration: 6–12 months (possibility of extension)

Start Date: ASAP

Overview

We are seeking an experienced Machine Learning Engineer to join our data science and AI engineering team on a contract basis in London. The ideal candidate will be responsible for designing, developing, and deploying machine learning models and scalable data pipelines that support advanced analytics and intelligent automation initiatives.

This role offers a hybrid work arrangement , combining flexibility with collaboration, and is ideal for a contractor who thrives in fast-paced, data-driven environments.

Key Responsibilities

• Design, build, and deploy machine learning models and AI-driven solutions to address business challenges.
• Collaborate with data scientists to transition prototypes into production-ready systems .
• Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment.
• Optimise model performance, scalability, and reliability using MLOps best practices.
• Work with large-scale structured and unstructured datasets for model training and validation.
• Implement model monitoring, versioning, and retraining processes to ensure continuous improvement.
• Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments.
• Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation.

Required Skills & Experience

• Proven experience (3–5+ years) as a Machine Learning Engineer , Data Scientist , or similar role.
• Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy).
• Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures .
• Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI).
• Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms.
• Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration.
• Knowledge of containerization and orchestration tools (Docker, Kubernetes).
• Experience integrating ML models into production environments via APIs or microservices.
• Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science , Data Science , Mathematics , or a related field.
• Familiarity with CI/CD pipelines for ML model deployment.
• Exposure to natural language processing (NLP) , computer vision , or reinforcement learning projects.
• Experience working in Agile/Scrum environments.

Contract Details

• Location: Hybrid – London (onsite 2–3 days per week)
• Type: Day-rate contract (Outside/Inside IR35 subject to assessment)
• Duration: 6–12 months (extension likely)
• Start Date: Immediate or within 2–4 weeks

Why Join

• Work with a talented, cross-functional AI and data engineering team.
• Contribute to cutting-edge ML solutions in a collaborative, innovation-driven environment.
• Hybrid flexibility with a strong London presence.

Job Title: Machine Learning Engineer

Location: London, UK (Hybrid – 2–3 days onsite per week)

Contract Type: Contract

Duration: 6–12 months (possibility of extension)

Start Date: ASAP

Overview

We are seeking an experienced Machine Learning Engineer to join our data science and AI engineering team on a contract basis in London. The ideal candidate will be responsible for designing, developing, and deploying machine learning models and scalable data pipelines that support advanced analytics and intelligent automation initiatives.

This role offers a hybrid work arrangement , combining flexibility with collaboration, and is ideal for a contractor who thrives in fast-paced, data-driven environments.

Key Responsibilities

• Design, build, and deploy machine learning models and AI-driven solutions to address business challenges.
• Collaborate with data scientists to transition prototypes into production-ready systems .
• Develop and maintain end-to-end ML pipelines for data ingestion, training, testing, and deployment.
• Optimise model performance, scalability, and reliability using MLOps best practices.
• Work with large-scale structured and unstructured datasets for model training and validation.
• Implement model monitoring, versioning, and retraining processes to ensure continuous improvement.
• Collaborate cross-functionally with engineering, data, and product teams to integrate ML solutions into production environments.
• Stay current with emerging trends in AI/ML technologies and contribute to innovation within the organisation.

Required Skills & Experience

• Proven experience (3–5+ years) as a Machine Learning Engineer , Data Scientist , or similar role.
• Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy).
• Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures .
• Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI).
• Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms.
• Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration.
• Knowledge of containerization and orchestration tools (Docker, Kubernetes).
• Experience integrating ML models into production environments via APIs or microservices.
• Excellent problem-solving, analytical, and communication skills.

Preferred Qualifications

• Bachelor’s or Master’s degree in Computer Science , Data Science , Mathematics , or a related field.
• Familiarity with CI/CD pipelines for ML model deployment.
• Exposure to natural language processing (NLP) , computer vision , or reinforcement learning projects.
• Experience working in Agile/Scrum environments.

Contract Details

• Location: Hybrid – London (onsite 2–3 days per week)
• Type: Day-rate contract (Outside/Inside IR35 subject to assessment)
• Duration: 6–12 months (extension likely)
• Start Date: Immediate or within 2–4 weeks

Why Join

• Work with a talented, cross-functional AI and data engineering team.
• Contribute to cutting-edge ML solutions in a collaborative, innovation-driven environment.
• Hybrid flexibility with a strong London presence.

A leading global hedge fund is looking to speak with Machine Learning researchers from any industry background who might be interested in applying their expertise to the trading domain. You'll be working alongside experienced portfolio management/trading teams to research and implement machine learning strategies to search for alphas in large, unstructured data sets.

Requirements:

-PhD in Machine Learning or related discipline.

-3+ years industry experience applying innovative ML research to real-world problems.

-Experience with large-scale data sets and unstructured data sources.

-Interest in quantitative trading.

-Hands-on coding experience in Python and/or compiled languages.