Machine Learning Jobs UK: ML engineer, data scientist and MLOps jobs in London and across the UK

Machine learning jobs in the UK: roles, skills and pay

What does a machine learning engineer do? A machine learning engineer builds, trains, evaluates and deploys models that learn from data, then keeps them working in production. In the UK the role usually needs strong Python, a framework such as PyTorch, cloud experience and good software engineering habits. Mid-level ML engineers in London commonly see advertised salaries of around £65,000 to £115,000.

Machine learning engineer jobs

The most advertised AI job title in the UK. Machine learning engineers sit between data science and software engineering: they turn a promising model into a reliable service. Typical work includes building training pipelines, feature engineering, model evaluation, latency and cost optimisation, and monitoring for drift. Increasingly, ML engineers also integrate large language models alongside classical models.

Skills UK employers ask for

• Python, plus PyTorch, TensorFlow or JAX, and scikit-learn for classical models
• SQL and data tooling such as Spark, dbt or a cloud data warehouse
• Cloud ML platforms: AWS SageMaker, Azure Machine Learning or Google Vertex AI
• Docker, Kubernetes, CI/CD and testing for ML code
• Evaluation design: choosing metrics that match the business problem

Common job titles

Machine learning engineer, ML engineer, AI engineer, applied ML engineer, senior ML engineer, staff ML engineer, ML engineering lead.

Data scientist jobs

Data scientists use statistics and machine learning to answer business questions: forecasting demand, predicting churn, pricing, experimentation and causal analysis. UK data science roles are found in almost every industry, from retail and banking to the NHS and government. Many now expect data scientists to prototype with generative AI as well as classical models, and to explain results clearly to non-technical colleagues.

Skills UK employers ask for

• Statistics, experimentation and A/B testing
• Python or R, SQL, and visualisation
• Supervised and unsupervised learning, time series and forecasting
• Communicating uncertainty and trade-offs to decision makers

MLOps and ML platform engineer jobs

MLOps engineers build the platforms that let AI teams ship safely and repeatedly: feature stores, model registries, deployment pipelines, GPU infrastructure, observability and cost control. As organisations move from one model to dozens, plus LLM workloads, MLOps and LLMOps roles have become some of the most sought after in UK AI hiring.

Skills UK employers ask for

• Kubernetes, Terraform and a major cloud provider
• MLflow, Kubeflow, Airflow or similar orchestration
• Model serving, monitoring, logging and alerting
• GPU scheduling and inference cost optimisation

AI research scientist and research engineer jobs

Research scientists and research engineers advance the state of the art: new architectures, training methods, alignment and safety, reinforcement learning and evaluation. The UK's research jobs cluster in London's King's Cross, Cambridge, Oxford and Edinburgh, at AI labs, big tech research groups, the UK AI Security Institute and universities. Research scientist roles usually expect a PhD or a strong publication record; research engineer roles weigh engineering ability more heavily.

Specialist ML jobs: computer vision, NLP and robotics

Specialist roles remain in strong demand: computer vision engineers for medical imaging, autonomy, manufacturing and retail; NLP engineers for search, document understanding and language products; and robotics and reinforcement learning engineers in Oxford, Cambridge, Bristol and London.

Machine learning salaries in the UK

How to get a machine learning job in the UK

1. Build one end-to-end project. Data in, model trained and evaluated, deployed behind an API, monitored. One complete project beats five notebooks.
2. Learn the foundations properly. Our plain-English guides on what machine learning is, how AI works and generative AI are a fast refresher before interviews.
3. Add LLM skills. Most ML roles now touch large language models. Our Building Agents in Claude Code and Advanced Claude Code modules are hands-on ways to get there.
4. Show you understand risk. Bias, explainability and data protection come up in UK interviews. See AI compliance, auditing and explainability.
5. Describe your work clearly. Use our guide on how to put AI skills on a CV.

Looking for roles built on large language models specifically? See generative AI and LLM jobs in the UK. Looking in the capital? See AI jobs in London.