Overview

Work on impactful public sector and mission-critical digital projects that make a positive difference to people’s lives. This organisation specialises in solving complex technical challenges using modern tools, emerging technologies, and innovative thinking.

As a Machine Learning Engineer (AI), you will research, develop, and test advanced AI algorithms, models, and technologies that enable organisations to automate processes and extract meaningful insights from data.

You will build complex machine learning models, design and manage MLOps pipelines, and ensure models remain performant, secure, and scalable in production environments. The role also includes mentoring junior team members, influencing technical decisions, and solving complex, non-routine technical problems.

The culture is inclusive, collaborative, and innovation-driven. The organisation values proactive, positive-thinking individuals who enjoy tackling technical challenges.

Role Objectives

Model Development and Delivery

Design, build, test, and deploy complex machine learning models.

Select appropriate modelling approaches for product and service use cases.

Ensure models meet performance, scalability, and quality standards.

MLOps and Deployment

Design and manage robust MLOps pipelines, including CI/CD processes.

Implement monitoring, retraining, and lifecycle management.

Deploy models into production environments and validate performance.

Ensure models remain safe, secure, and effective in live systems.

Advanced Technical Problem Solving

Act as a subject matter expert for complex, non-routine machine learning challenges.

Develop innovative solutions to high-risk or ambiguous problems.

Customise, optimise, retrain, and maintain existing models.

Integration and Collaboration

Work cross-functionally to integrate machine learning models into existing systems.

Collaborate with engineers, data scientists, and technical stakeholders.

Ensure production systems meet reliability and security standards.

Requirements

Broad expertise in machine learning algorithms, frameworks, and best practices.

Experience planning and conducting research activities within AI or generative AI domains.

Ability to evaluate emerging AI technologies for business relevance and feasibility.

Experience delivering complex proofs of concept and experimental prototypes.

Recognised technical authority within AI or generative AI.

Strong data science capability supporting model development.

Proven experience building, deploying, and managing complex machine learning systems.

Inclusion Statement.

Candidates are encouraged to apply even if they do not meet every requirement. The organisation values diversity and welcomes applications from individuals across all backgrounds, including underrepresented communities.

Reasonable adjustments can be made throughout the recruitment process to support individual needs.

Security RequirementsThis role requires eligibility for government-level security clearance. Candidates must have the legal right to work in the UK without sponsorship and meet residency requirements for clearance eligibility.

Benefits

Competitive salary reviewed annually.

Employer pension contribution starting at 5 percent, increasing with tenure.

Group Life Assurance.

25 days annual leave plus bank holidays, with option to buy or sell leave.

Two paid volunteering days per year.

Fully funded professional certifications and paid study leave.

Annual personal development allowance.

Access to coaching and professional training.

Private medical insurance.

Hybrid working with home office allowance.

Cycle to Work scheme.