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Machine Learning Engineer

Role overview

Summary

This role focuses on designing, developing, and deploying data science and AI/ML solutions at Sage Publishing. You will work in a multi-functional team to implement MLOps practices and enhance existing solutions, while also acting as a trusted advisor on MLOps Engineering across the business.

Qualifications

  • Demonstrated experience of designing and implementing MLOps principles, standards, frameworks, guidelines, and engineering infrastructure.
  • 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.
  • Proficiency in programming languages such as Python, R, Java, C#.
  • Preferred: Excellent relationship building skills with the ability to gain trust and influence at senior level.

Responsibilities

  • Design, implement, and evolve MLOps principles, standards, frameworks, and engineering platforms.
  • Develop production data science and AI/ML solutions focusing on NLP, recommender systems, and knowledge graphs.
  • Monitor and analyze the performance of deployed models and systems, implementing optimizations as required.
  • Coach and guide more junior members of the team.

Key facts

Hard skills

Other skills

  • Communication
  • Problem Solving
  • Relationship Building

About the company

SAGE Publishing logo

SAGE Publishing

  • News & Publishing
  • 1,001–5,000
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, 24-year-old Sara Miller McCune founded Sage in 1965. Today, we are controlled by a group of trustees charged with maintaining our independence and mission indefinitely. Driven by the belief that social and behavioral science has the power to improve society, we focus on publishing impactful research and enabling robust research methodology. We produce high-quality educational resources that support instructors to prepare the citizens, policymakers, educators and researchers of the future. Sage is committed to building an inclusive organization where all individuals are treated with fairness and respect, regardless of age, ability, gender, marriage and partnership status, pregnancy and parental responsibilities, race, religion and belief, socio-economic background, or sexual orientation. Diversity is one of the cornerstones of a vibrant culture and we are undertaking work to build a Sage that is more equitable and representative of the communities we serve and of which we are part. As well as driving change within Sage, we are also passionate about supporting diversity, equity and inclusion in wider society through our publishing activities. To find out more, visit https://group.sagepub.com/dei

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Job description

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. 

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). 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.

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