Machine Learning Engineer · London, United Kingdom

Sage Pub; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

25 days annual leave + bank holidays

2 floating personal days

Hybrid working

Private medical cover

Tuition scheme

Company loans

Job summary

Sage Publishing seeks a self-motivated Machine Learning Engineer with a focus on MLOps, NLP, knowledge graphs, and Azure services. You will design, develop, and deploy Data Science & AI/ML solutions, building engineering infrastructure in a greenfield environment.

You will design and evolve MLOps standards, implement production ML solutions, monitor model performance, and collaborate with multi-disciplinary teams to deliver business outcomes. Hybrid work, with in-office days and remote support.

Qualifications

• Demonstrated experience designing and implementing MLOps principles, standards, and platforms.
• Experience delivering scalable production ML solutions using NLP, recommender systems, and knowledge graphs.
• Strong experience with Azure DevOps or similar CI/CD pipelines for ML deployments.
• Solid data engineering foundation including ETL pipelines and data storage design.
• Proficiency in Python and at least one of Java or C#.

Responsibilities

• Design, implement, and evolve MLOps frameworks and platforms for enterprise data science initiatives.
• Develop production ML solutions focusing on NLP, recommender systems, and knowledge graphs.
• Implement end-to-end model lifecycle management including versioning, auditing, and security.
• Monitor deployed models and optimize performance; escalate ML engineering issues as needed.
• Collaborate across departments to drive ML initiatives and act as a trusted advisor.
• Mentor junior engineers and communicate ML concepts to non-technical audiences.

Skills

Python

NLP

MLOps

Azure

CI/CD

Knowledge graphs

Recommender systems

C#

Java

Tools

Azure DevOps

Azure Data Lake

Azure SQL Database

Job description

About Sage:

Sageis 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.

Our guaranteed independence means we’re free to:

• Do more – supporting an equitable academic future, furthering disciplines that drive social change, and helping social and behavioural science make an impact
• Work together – building lasting relationships, championing diverse perspectives, and co-creating resources to transform teaching and learning
• Think long-term – experimenting, taking risks, and investing in new ideas

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).

We’re committed to making our recruitment process accessible and inclusive. If you’d like to request reasonable adjustments, please email [e-mail]. Please note we only accept applications via email if an adjustment has been agreed.

Closing date for applications:

November 21, 2026

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.