Salary: £34,000 - 69,000 per year
Requirements:
- MSc or BSc in Computer Science, Data Science, Bioinformatics, Engineering, or a related field, or equivalent experience
- Proven experience designing and deploying MLOps pipelines, including MLflow, Azure ML, Azure DevOps, or similar tools
- Strong programming skills in Python and familiarity with common ML/AI libraries, including Scikit-learn, TensorFlow, and Keras
- Experience implementing machine learning and large language models, including deployment, monitoring, and retraining
- Familiarity with software engineering guidelines, including version control, Git, CI/CD, containerisation, Docker, and workflow orchestration
- Knowledge of cloud platforms and scalable compute environments, with Azure preferred
- Understanding of data governance, model documentation, and reproducibility in a regulated or research-heavy context
- Ability to align machine learning initiatives with business objectives in a scientific or regulated environment
Responsibilities:
- Design, build, and maintain resilient Machine Learning Operations pipelines that support the complete lifecycle of AI models, from creation to implementation and supervision
- Ensure the successful deployment of machine learning and large language models in practical operational settings, transforming research findings into functional business tools
- Support the development and evaluation of ML models, including both standard machine learning and neural network-focused models, as requested by R&D teams
- Develop standardised, reusable workflows that can be applied across different projects and scientific areas
- Collaborate with scientists and engineers to incorporate AI solutions into daily R&D tasks
- Implement tools for version control, testing, and continuous integration to ensure quality, security, and traceability of AI solutions
- Develop automated reporting systems that make results from AI models easier to interpret, share, and act on
Technologies:
- AI
- Azure
- CI/CD
- Cloud
- DevOps
- Docker
- Git
- Support
- Keras
- Machine Learning
- Network
- Python
- Security
- TensorFlow
More:
We are a full-time R&D-focused team based in East Molesey, England, United Kingdom, seeking an experienced Senior MLOps Engineer to bridge machine learning engineering with applied data science. We work closely with scientific and operational teams to improve the robustness, scalability, and reliability of AI tools, while driving automation and standardisation across the ML lifecycle to enable faster, data-informed decision-making and innovation. This role offers the opportunity to contribute significantly to the development, deployment, and advancement of machine learning and AI systems in a scientific and regulated environment.