Excellent Salary Plus Benefits.
London / Hybrid / Remote.
Competitive daily rate.
Were 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.
Youll 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.
Key Responsibilities Include
- 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.
What Were Looking For
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.
This is a unique opportunity to engineer AI systems that directly impact digital services, working with modern platforms, meaningful challenges and technology that benefits millions of users.
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