Machine Learning Engineer

We’re AioiR&D Lab
– an AItech hub in one of the fastest-growing insurance companies.

We research and develop AI systems thatcatapultinsurance fromaslow-moving, traditionalpastintoa data-driven,technology-lead and society-defining future.

We’re looking for dynamic, driven professionals like you to help evolve our business in new directions. You’ll need first-class credentials and a proactive attitude to help us drive the change the underpins our mission.
We are seeking to recruit two Machine Learning Engineer's to join our team on 18-month fixed-term contracts. These are hybrid roles, offering a combination of at home and on-site working.

As a Machine Learning Engineer, you will support the development of a privacy-preserving generative AI ecosystem designed to protect personal and sensitive corporate data by design, including data residency, anonymisation and secure deployment principles. Working within a multidisciplinary and multi-partner environment, the postholder will help translate research and technical concepts into dependable systems and components that can be used in live settings, while also supporting the broader technical development of the Lab and its collaboration with CODAS and other project partners.

BE THE NEXT BIG THING, NOW.

• Design, develop, test and maintain machine learning and AI software in support of the CODAS project and related R&D Lab initiatives.
• Contribute to the delivery of technical components for a sovereign AI ecosystem, including ML services, data processing pipelines, evaluation tooling and deployment-ready applications.
• Support the translation of research outputs into robust, maintainable and operationally viable systems.
• Work with internal colleagues and external project partners to understand technical requirements, constraints and delivery priorities.
• Help adapt AI and ML approaches to privacy-sensitive, security-conscious and regulated deployment contexts.
• Contribute to the integration of technical solutions into project infrastructure, workflows and partner environments.
• Troubleshoot technical, data and integration issues arising during development and deployment.
• Support the development and improvement of internal tooling, engineering standards, reusable frameworks and deployment practices across the Lab.
• Communicate technical trade-offs, risks and progress clearly to both technical and non-technical stakeholders.

• Degree in Computer Science, Mathematics, Statistics, Physics, Engineering or another relevant STEM discipline, or equivalent practical experience.
• 2+ year work experience in relevant field.
• Strong software engineering capability in Python, including writing clean, maintainable, well-tested and well-documented code.
• Experience developing and deploying machine learning, AI or data-driven systems in production or near-production settings.
• Familiarity with Linux, Docker, version control, CI/CD and service-oriented deployment practices.
• Experience working across the lifecycle from experimentation and prototyping through to integration and operationalisation.
• Ability to work effectively in technically complex and ambiguous environments involving multiple stakeholders.
• Strong communication skills, including the ability to explain technical issues and trade-offs clearly to non-specialists.

• Experience with generative AI systems, LLM-enabled applications or evaluation pipelines.
• Experience with privacy-preserving, secure or compliance-sensitive technical environments.
• Experience with cloud platforms, MLOps tooling, model serving or platform engineering.
• Experience with data pipelines, APIs, system integration or user-facing AI applications.
• Experience working in multi-partner…