Machine Learning Engineer

Reporting to a senior technology leader, you will work closely with data, product and engineering colleagues to take machine-learning solutions from concept through to reliable, scalable deployment. As a Machine Learning Engineer, you will have real ownership in a greenfield environment, improving how models are built, governed, monitored and used across the organisation. The Opportunity

This is more than a model-building role. You will create the engineering foundations that allow AI solutions to deliver lasting value in production.

• Design and develop robust MLOps practices, platforms and standards.
• Build and deploy AI/ML solutions with a focus on natural-language applications, personalisation and semantic/graph-based data.
• Improve the end-to-end model lifecycle, including version control, deployment, monitoring, security and auditability.
• Monitor live models and optimise performance, reliability and cost.
• Partner with engineers, data specialists and non-technical stakeholders to solve meaningful business problems.
• Act as a technical escalation point for deployed ML solutions.
• Share knowledge and mentor colleagues, developing their engineering capability.
• Keep abreast of developments across AI, cloud and MLOps, bringing practical improvements into the team.

What’s in it for you?

• £75,000 - £80,000 salary.
• Hybrid working and home-working support.
• 25 days’ annual leave plus bank holidays and additional personal days.
• Pension and employee loan schemes.
• Funding and support for training, professional qualifications and continued learning.
• A supportive, inclusive culture with genuine scope to influence the organisation’s AI direction.

• Proven experience building and deploying production machine-learning solutions.
• Strong practical knowledge of MLOps, including model deployment, monitoring, governance and CI/CD.
• Experience with Microsoft Azure and cloud-based data services.
• Strong Python skills; experience with another language such as R, Java or C# is also welcome.
• Sound understanding of data engineering, ETL pipelines and data security.
• Excellent problem-solving and communication skills, with the ability to work across technical and non-technical teams.
• Experience with NLP, recommender systems, knowledge graphs or semantic technologies.
• Familiarity with Azure DevOps or comparable CI/CD tooling.
• Experience with Azure Data Lake, Azure SQL Database or similar cloud storage platforms.
• Previous mentoring or coaching experience.
• A degree in Computer Science, Data Science, Engineering or a related discipline, or equivalent commercial experience.