Machine Learning Engineer in London

About Sage: Sage is a global academic publisher of books, journals, and library resources with a growing range of technologies to enable discovery, access, and engagement. Believing that research and education are critical in shaping society, Sara Miller McCune founded Sage in 1965. Today, we are controlled by a group of trustees charged with maintaining our independence and mission indefinitely.

About The Role: Sage Publishing seeks a self-motivated Machine Learning Engineer with a focus on MLOps (Machine Learning Operations), NLP (Natural Language Processing), knowledge graphs, and Azure services. This role involves designing, developing, and deploying Data Science & AI/ML (Artificial Intelligence/Machine Learning) solutions, products, and engineering infrastructure as part of a multi-functional team, working as a self-starter in a greenfield environment, and managing multiple deliverables to deliver high-quality results that drive business outcomes.

Your New Role:

• Design, implement, and evolve MLOps principles, standards, frameworks, and engineering platforms to support enterprise data science & AI/ML initiatives.
• Work multi-functionally to develop production data science and AI/ML solutions, with a focus on NLP, recommender systems, knowledge graphs, that address complex business needs.
• Implement MLOps practices to streamline the model lifecycle from development to deployment and monitoring, with a focus on auditability, versioning, data security.
• Monitor and analyze the performance of deployed models and systems, and implement optimizations as required.
• Act as point of escalation for ML Engineering related issues with deployed solutions.
• Remain up-to-date with the latest trends in AI/ML, MLOps, and Azure services and apply them to enhance existing solutions.
• Build relationships across the department and the wider Company to be viewed as a trusted advisor on matters of MLOps Engineering for deliverables and initiatives from departments across the business.
• Coach and guide more junior members of the team / team members with other technical backgrounds.
• Communicate effectively about MLOps and existing solutions with technical and non-technical audiences.

Can you be our new Machine Learning Engineer?

• Demonstrated experience of designing and implementing MLOps principles, standards, frameworks, guidelines, and engineering infrastructure.
• Demonstrated experience of working multi-functionally to deliver scalable production solutions using data science and AI/ML tools and techniques, and Azure services.
• Strong applied understanding of NLP, recommender systems, and knowledge graphs.
• Experience with Azure DevOps or similar CI/CD/CT pipelines for deploying AI/ML solutions.
• Strong understanding of data engineering principles and ETL pipelines.
• Proficiency in programming languages such as Python, R, Java, C#.
• Familiarity with cloud-based data storage technologies like Azure Data Lake and Azure SQL Database.
• Excellent relationship building skills with the ability to gain trust and influence at senior level.
• Experience of coaching/mentoring more junior engineers or others with different technical backgrounds.
• Excellent problem-solving abilities and strong communication skills.

Overview of benefits:

• 25 days annual leave (plus bank holidays) with 2 additional floating personal days.
• Hybrid working up to 2 days per week in office and a home working allowance.
• Life assurance, income protection, and travel insurance.
• Private medical cover and access to the company doctor.
• Tuition scheme and support for pursuing professional qualifications, including access to Sage books and journals.
• Variety of snacks and beverages available in the office.
• Healthy lifestyle reimbursement and anniversary trips.
• Access to Company loans (season ticket loan, rental deposit loan, cycle loan).

We’re a Disability Confident Employer (Level 1). If you’d like to apply under this scheme, please let us know in your application. We’re committed to making our recruitment process accessible and inclusive. If you’d like to request reasonable adjustments, please email humanresources@sagepub.co.uk. Please note we only accept applications via email if an adjustment has been agreed.

Closing date for applications: November 21, 2026. To ensure we can give each application the attention it deserves, we may consider bringing the closing date forward. Therefore, we encourage you to submit your application as soon as possible to ensure it is considered.

Diversity, Equity, and Inclusion: At Sage, we are committed to building a diverse and inclusive team and to sustaining a culture that celebrates diversity, encourages authenticity, and builds a deep sense of belonging. We encourage applications from all members of society irrespective of age, disability, sex or gender identity, sexual orientation, colour, race, nationality, ethnic or national origin, religion, or belief as crafting value through diversity is what makes us strong.