Machine Learning Engineer Jobs in the UK (No ghost jobs, direct from employers)
Machine learning engineer jobs across the UK, checked every hour. Pay where listed, posting age, company reviews and a ghost-job check on every posting.
253 jobs found
- 4 days agoLow ghost riskSAGE PublicationsHybridLondon, ENG$89K - 104KMid-level
- 2 days agoLow ghost riskKplerOn-siteUnited Kingdom$85K - 120KLead
- 1 week agoModerate ghost riskJust Eat Takeaway.comHybridAmsterdam Office$85K - 120KSenior
- 1 week agoModerate ghost riskJust Eat Takeaway.comHybridBerlin Office$85K - 115KSenior
- 1 week agoLow ghost riskASOSOn-siteHampstead Road$65K - 95KSenior
- 3 days agoLow ghost riskPhysicsXHybridLondon, ENG$85K - 120KSenior
- 1 week agoLow ghost riskCapgemini Holding IncHybridLondon, ENG$85K - 120KSenior
- 1 week agoLow ghost riskASOSOn-siteHampstead Road$70K - 100KSenior
- 1 week agoLow ghost riskMoody's CorporationHybridLondon, ENG$100K - 150KLead
- 1 day agoLow ghost riskApple Inc.On-siteCambridge, England$30K - 50KJunior
- 1 week agoLow ghost riskEncordOn-siteLondon, ENG$85K - 120KSenior
- 1 week agoModerate ghost riskASOSOn-siteHampstead Road$65K - 95KSenior
- 1 week agoLow ghost riskASOSOn-siteHampstead Road$70K - 100KSenior
- 14 hours agoLow ghost riskApple Inc.On-siteLondon, ENG$30K - 50KJunior
- 1 week agoModerate ghost riskDepopHybridLondon, ENG$85K - 120KSenior
- 2 days agoLow ghost riskNominalOn-siteLondon, ENG$100K - 150KMid-level
- 1 week agoModerate ghost riskTrainlineOn-siteLondon, ENG$75K - 105KSenior
- 2 weeks agoModerate ghost riskASOSOn-siteHampstead Road$60K - 90KMid-level
- 1 week agoModerate ghost riskJane StreetOn-siteLondon, ENG$120K - 180KSenior
- 2 weeks agoLow ghost riskHSBCOn-siteLondon, ENG$85K - 120KSenior
Why this job matches
See how well your resume fits this job and what it is missing.
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.
Department Technology Location London, United Kingdom Salary £70,000 - £80,000/year Remote Status Hybrid Employment Type Full-time Employment Level Mid Level
Browse Open Roles
- Technology Product Manager, Data Science
Technology · London, United Kingdom
- Senior Manager, Technology Product Management, Data
Technology · London, United Kingdom
- Senior Technology Product Manager, Business Insights
Technology · London, United Kingdom
More jobs
London, United Kingdom
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. Our mission is building bridges to knowledge - supporting the development of ideas through the research process to scholarship that is certified, taught, and applied.
Learn about Sage | About our companies | Open editor positions
Sage is committed to the full inclusion of all qualified applicants. Accommodations will be made for any part of the interview process.
Company Reviews
Employee reviews3.8
771 Reviews- Decent place2026-03-02T03:14:18.087
Pros: Great people, Fun offices (at the time) Doing meaningful work
Cons: Quite slow moving, design by committee attitude when I was there.
- Nice environment2026-02-28T08:07:55.590
Pros: Friendly environment, timely salary, good work life balance.
Cons: You cannot expect much in term of income.
- Not a good company to work for anymore2026-02-08T21:57:40.040
Pros: Trying to incorporate AI in the product
Cons: very low salary, no snacks, no lunch
Related jobs by role, place and level
Every page lists all openings, with likely ghost jobs flagged. Checked every hour.
More machine learning engineer jobs
Jobs in the UK
Frequently asked questions about machine learning engineer jobs in the UK
What is a ghost job?
A ghost job is a posting for a role the company isn't actively hiring for. Some stay up after the company fills the role. Others collect resumes for an opening that may never come.
You spend an evening tailoring an application, and nobody on the other side is looking for you.
What do machine learning engineer jobs in the UK pay?
Few of these postings list pay. Where an employer posts a range, the job card shows it; where it doesn't, the card shows an estimate and says so. Counting those estimates, the median here is about $102,000 a year (in US dollars).
How many machine learning engineer jobs in the UK are there?
At our last count there were about 250 open postings. The list on this page is live, so the count above it is the current one.
How does Enhancv spot a ghost job?
Every posting goes through five checks: how long it has been up, whether a salary is posted, what employees say about the company, how specific the description is and whether it lists real requirements. Each job shows the checks it passed and the ones it didn't.
How fresh are the job postings?
Enhancv checks postings every hour, and every job shows how long ago it went up. Most hires happen within 30 days of posting. A listing that's been open for two months raises its ghost job risk.













