AI Engineer / Machine Learning Engineer.

We're now looking for a skilled AI Engineer / Machine Learning Engineer to support the next phase of AI-enabled digital service delivery.

This is an opportunity to design, build and operate intelligent, production-grade AI systems that power digital services which are simpler, clearer and faster and that genuinely meet real user needs at national scale.

You'll play a key role in developing scalable machine learning and generative AI solutions, embedding them into secure cloud environments, and working closely with multidisciplinary teams to translate complex requirements into reliable, real-world AI capabilities., * Designing, building and deploying scalable machine learning, deep learning and generative AI systems for production digital services.

• Developing robust data pipelines, model training workflows and inference services across cloud-based environments.
• Collaborating with data scientists, engineers, product managers, designers and policy stakeholders to deliver end-to-end AI solutions.
• Implementing AI-enabled capabilities such as intelligent automation, natural language processing, prediction and decision support.
• Ensuring AI systems are secure, observable, maintainable and aligned with governance, privacy and responsible AI standards.
• Supporting experimentation, evaluation, monitoring and continuous improvement of models in live production environments.
• Optimising model performance, scalability, reliability and cost efficiency.
• Staying current with emerging AI tooling, architectures, frameworks and engineering best practice.

Experience & Skills

• Strong proficiency in Python and modern machine learning frameworks.
• Proven experience building, deploying and maintaining machine learning or deep learning systems in production.
• Knowledge of natural language processing, transformers or generative AI architectures.
• Experience working with large-scale datasets, data pipelines and cloud data platforms.
• Understanding of software engineering best practice, testing, versioning and CI/CD for ML systems.
• Familiarity with MLOps principles including monitoring, evaluation, retraining and lifecycle management.
• Ability to communicate complex technical concepts clearly to a wide range of stakeholders.
• Experience collaborating within multidisciplinary digital or product teams.
• Commitment to ethical, transparent and responsible AI engineering.
• Comfortable working in fast-moving, evolving and sometimes ambiguous environments.

Desirable (but not essential):

• Experience integrating large language models via APIs or open-source frameworks.
• Fine-tuning, evaluating or optimising generative AI systems.
• Experience with containerisation, orchestration and scalable cloud infrastructure.
• Knowledge of reinforcement learning, graph machine learning or advanced deep learning approaches.
• Exposure to observability, model governance and AI assurance practices.
• Experience within government, public sector or other regulated environments.
• Mentoring engineers or contributing to AI engineering standards and capability development.