Lead Machine Learning Engineer

Line manage and develop ML engineers, providing coaching, mentoring, feedback and performance support; contributing to hiring, onboarding and capability development within the ML engineering function.

Maintain a meaningful individual contribution to technical delivery on selected projects, alongside leadership responsibility across multiple engagements.

Collaborate with the Lead ML Scientist and Principal Engineer to establish and embed best practice in ML engineering across the Lab.

Lead multidisciplinary teams of ML engineers[A1.1][A1.2], ML scientists and software engineers, ensuring effective delivery practices, team communication and continuous improvement.

Mentor and develop junior ML engineers, including supporting their technical training and the ongoing development of ML engineering capability across the Lab.

Support solution design and provide technical leadership to ensure ML systems are robust, scalable and maintainable.

Provide oversight, coordination and quality assurance across multiple concurrent projects, identifying and managing technical and delivery risks across engagements, escalating where appropriate.

Contribute hands-on to delivery where required, particularly on complex or high-priority engagements.

Lead use case discovery and help shape AI and ML opportunities with relevant stakeholders.

Support pre-sales activity in collaboration with the commercial team, including technical scoping and solution shaping.

Partner with the Project Management function to scope, plan and support delivery engagements.

Oversee the maintenance and continuous improvement of deployed solutions.

Drive reuse of shared frameworks, standards and tooling across projects.

Communicate technical decisions, risks and concerns clearly to non-technical audiences.

• PhD or MSc in Computer Science, Mathematics, Statistics, Engineering, Physics or another relevant STEM discipline, or equivalent practical experience. • Extensive years of experience in machine learning engineering, software engineering, or a related technical role, including experience delivering production-grade ML systems and leading technical work across teams or projects. • Strong software engineering background, with experience building and delivering machine learning or data-driven systems in production or near-production environments. • Experience leading or managing machine learning engineers or other technical contributors in a delivery-focused setting. • Experience supporting pre-sales, technical discovery or opportunity shaping in collaboration with commercial or business development teams. • Ability to provide technical leadership across solution design, engineering quality, deployment approaches and ongoing maintenance of ML-enabled systems. • Experience working across the lifecycle of AI or ML solutions, from use case discovery and scoping through to delivery, deployment and continuous improvement. • Strong understanding of engineering best practice, including code quality, testing, documentation, maintainability and reuse. • Experience working collaboratively in multidisciplinary teams, including ML engineers, ML scientists, software engineers, project managers and non-technical stakeholders. • Experience with cloud platforms, CI/CD, containerisation, model deployment and operational support for production systems. • Ability to communicate technical decisions, risks and trade-offs clearly to both technical and non-technical audiences. • Strong problem-solving, prioritisation and judgement in ambiguous, fast-moving environments. • Experience contributing hands-on to technical delivery while also leading multiple projects or workstreams in parallel.