503 Ethical AI jobs in the United Kingdom

• Develop, refine, and enforce comprehensive ethical principles and guidelines for AI development and deployment.
• Conduct in-depth ethical risk assessments and bias audits for new and existing AI models and applications.
• Collaborate with cross-functional teams to integrate ethical considerations into design, development, testing, and operational processes.
• Provide expert guidance and training on AI ethics, fairness, accountability, and transparency to internal stakeholders.
• Stay current with evolving global regulations, industry best practices, and societal expectations regarding AI ethics.
• Research and propose innovative solutions to address complex ethical challenges in AI, such as algorithmic bias, privacy concerns, and societal impact.
• Engage with external stakeholders, including policymakers, academics, and civil society organizations, to contribute to the broader discourse on AI ethics.
• Develop and implement mechanisms for monitoring and evaluating the ethical performance of deployed AI systems.
• Champion a proactive and preventative approach to ethical AI development across the organization.

• Advanced degree (Master's or Ph.D.) in Philosophy, Ethics, Law, Computer Science, Social Sciences, or a related field with a specialization in AI ethics or technology ethics.
• Demonstrated experience in developing and implementing ethical frameworks, policies, or standards, preferably in the tech industry or with AI-related projects.
• Strong understanding of AI technologies, machine learning principles, and their potential ethical implications.
• Expertise in areas such as algorithmic bias, fairness metrics, explainable AI (XAI), data privacy, and AI governance.
• Exceptional analytical, critical thinking, and problem-solving skills.
• Excellent written and verbal communication skills, with the ability to influence and engage diverse audiences.
• Proven ability to lead initiatives and drive consensus in complex, multi-stakeholder environments.
• A deep commitment to advancing responsible and beneficial AI for all.

• Develop, implement, and oversee comprehensive AI ethics frameworks, policies, and guidelines.
• Conduct rigorous ethical impact assessments for new AI products and features.
• Collaborate closely with AI researchers, data scientists, engineers, and product managers to embed ethical considerations throughout the AI lifecycle.
• Provide expert guidance and training on AI ethics to various stakeholders.
• Stay abreast of the latest research, regulations, and best practices in AI ethics and responsible AI.
• Engage with external bodies, academics, and industry groups to contribute to the broader discourse on AI ethics.
• Monitor and audit AI systems for fairness, bias, transparency, and accountability.
• Advise on data governance and privacy considerations related to AI systems.
• Manage and mentor junior members of the Responsible AI team.

• Advanced degree (Master's or PhD) in a relevant field such as Ethics, Philosophy, Computer Science, Law, Social Science, or a related discipline.
• A minimum of 5-7 years of experience specifically in AI ethics, responsible AI, or technology ethics.
• Demonstrated understanding of AI/ML concepts and their ethical implications.
• Proven experience in developing and implementing ethical frameworks and policies.
• Excellent analytical, critical thinking, and problem-solving skills.
• Strong communication and interpersonal skills, with the ability to engage effectively with diverse audiences.
• Experience with data privacy regulations (e.g., GDPR) is highly desirable.
• Familiarity with bias detection and mitigation techniques in AI systems.
• Ability to work independently and collaboratively in a fast-paced environment.

Job title: Machine Learning Engineer

Locations: Manchester or Haywards Heath (hybrid working)

Role overview

Markerstudy Group have an exciting opportunity for a machine learning engineer to fill out the automation, pipelining, DevOps, and modelling aspects of Markerstudy’s market-leading technical modelling and pricing team. You will productionise novel insurance modelling processes as an automated machine learning pipeline within a cloud-based environment.

Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. Most of Markerstudy’s business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury’s, O2, Halifax, AA, Saga and Lloyds Bank to list a few.

As a Machine Learning Engineer, you will help build and maintain the pricing team’s MLOps and ML Lifecycle environment to support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical modelling and pricing function.

Key Responsibilities:

• Build an MLOps / DevOps environment to support machine learning automation
li>Build the pipelines that automate the regular model update and monitoring processes
• Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation, and communication processes.
• Work closely with the data science team to integrate modelling approaches and techniques

Key Skills and Experience:

• Previous experience as a DevOps / MLOps engineer
• Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud)
• Understanding of machine learning models and the modelling process, from data ingestion and cleaning to deployment and modelling – from the ground-up, not only through the use of packages and libraries
< i>Proficient at communicating results in a concise manner both verbally and written
• Previous industry experience in a STEM role or educated to the Master’s level in a STEM or DS / ML / AI or maths-based discipline.

Behaviours:

< i>Collaborative and team player
• Logical thinker with a professional and positive attitude
• Passion to innovate and improve processes
• Strong grasp of industry standards, and proficient in either Python, R, or both

Job title: Machine Learning Engineer

Locations: Manchester or Haywards Heath (hybrid working)

Role overview

Markerstudy Group have an exciting opportunity for a machine learning engineer to fill out the automation, pipelining, DevOps, and modelling aspects of Markerstudy’s market-leading technical modelling and pricing team. You will productionise novel insurance modelling processes as an automated machine learning pipeline within a cloud-based environment.

Markerstudy is a leading provider of private insurance in the UK, insuring around 5% of the private cars on the UK roads, 20% of commercial vehicles and over 30% of motorcycles in total premium levels of circa £1b. Most of Markerstudy’s business is written as the insurance pricing provider behind household names such as Tesco, Sainsbury’s, O2, Halifax, AA, Saga and Lloyds Bank to list a few.

As a Machine Learning Engineer, you will help build and maintain the pricing team’s MLOps and ML Lifecycle environment to support the creation of pipelines by automating the sophisticated machine learning models and processes that underpin our market-leading technical modelling and pricing function.

Key Responsibilities:

• Build an MLOps / DevOps environment to support machine learning automation
li>Build the pipelines that automate the regular model update and monitoring processes
• Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation, and communication processes.
• Work closely with the data science team to integrate modelling approaches and techniques

Key Skills and Experience:

• Previous experience as a DevOps / MLOps engineer
• Experience in Azure ML or databricks, or similar industry approved technology stack (i.e. AWS, Kubernetes and Docker, Google Cloud)
• Understanding of machine learning models and the modelling process, from data ingestion and cleaning to deployment and modelling – from the ground-up, not only through the use of packages and libraries
< i>Proficient at communicating results in a concise manner both verbally and written
• Previous industry experience in a STEM role or educated to the Master’s level in a STEM or DS / ML / AI or maths-based discipline.

Behaviours:

< i>Collaborative and team player
• Logical thinker with a professional and positive attitude
• Passion to innovate and improve processes
• Strong grasp of industry standards, and proficient in either Python, R, or both

Machine Learning Engineer and Data Engineer

Location: London

Type: Full-time | Permanent | Office based

Salary: up to £100,000 (ML Engineer) and up to £80,000 (Data Engineer)

About Us

We’re an early-stage startup on a mission to. As we scale, we’re looking for a Machine Learning Engineer and Data Engineer who are excited to build real-world products from the ground up, shape the future of our technology, and make a measurable impact.

The Role

You’ll play a key role in designing, building, and deploying ML models that power our core product. This isn’t just about research — it’s about turning ideas into features customers love. You’ll work closely with our founding team, own projects end-to-end, and help set the standard for engineering practices as we grow.

What You’ll Do

• Design, train, and deploy machine learning models to solve real-world problems.
• Collaborate with product and engineering teams to integrate ML into customer-facing features.
• Build scalable data pipelines and infrastructure to support model training and inference.
• Experiment with new algorithms and techniques, bringing the latest research into production.
• Monitor and optimise models for performance, accuracy, and efficiency.
• Contribute to technical decisions that balance immediate needs with long-term scalability.
• Help shape our technical culture, processes, and roadmap as an early team member.

What We’re Looking For

• 2+ years’ experience as a Machine Learning Engineer, Data Scientist, or similar role.
• Strong background in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience with building and deploying ML models into production.
• Knowledge of APIs, data pipelines, and cloud infrastructure (AWS, GCP, or Azure).
• Strong problem-solving skills and ability to work independently in a fast-paced environment.
• Curiosity, openness, and a willingness to experiment and learn.
• Excellent communication skills for explaining complex concepts to technical and non-technical audiences.

Nice to Have

• Experience working in a startup or high-growth tech environment.
• Familiarity with AI-assisted coding tools (e.g. GitHub Copilot, Cursor).

Who We Are

At Ultralytics , we relentlessly drive innovation in AI, building the world's leading open-source models . We're looking for passionate individuals obsessed with AI, eager to make a global impact, and ready to excel in a dynamic, high-energy environment. Join our team and help shape the future of Vision AI .

Location and Legalities

This full-time Machine Learning Engineer position is based onsite in our brand-new Ultralytics office in London, UK. Applicants must have legal authorization to work in the UK, as Ultralytics does not provide visa sponsorship.