MACHINE LEARNING RESEARCH ENGINEER
Salary: £48,330 - £62,835
Location: Cambridge - Triangle/ Hybrid (2 days per week in the office)
Contract: Full Time (35 hours per week), Permanent
Shape the future of AI-powered learning solutions with Cambridge University Press & Assessment, a world-leading academic publisher and assessment organisation, and a proud part of the University of Cambridge.
This is an exciting opportunity for Machine Learning Research Engineers to join our innovative Applied AI team. You'll contribute to developing, deploying, and maintaining cutting-edge AI capabilities that drive the success of Cambridge English's products and services.
About the Role
As a Machine Learning Research Engineer, you will play a pivotal role in driving innovation and advancing AI-powered solutions that enhance Cambridge English products. Your expertise will contribute to the continuous improvement of existing models and the development of cutting-edge technologies that address future business needs.
Key Responsibilities:
1. Develop, deploy, and maintain scalable AI-powered solutions for Cambridge English products.
2. Optimise and modularise models for reusability and performance.
3. Collaborate with product, validation, and business teams to transform capabilities into impactful product features.
4. Stay at the forefront of AI and machine learning trends to position Cambridge as a leader in AI-driven assessment and learning.
5. Plan, prioritise, and manage own tasks aligned with business objectives.
We are also looking for 2 Junior Machine Learning Research Engineers (permanent) and 2 Senior Machine Learning Research Engineers (1x permanent, 1x fixed-term). Please visit the linked job postings to apply for these roles.
About You
To thrive in this role, you'll have a passion for AI-driven innovation and the ability to turn ideas into scalable solutions.
Essential Qualifications & Skills:
6. Master's degree ( or equivalent qualifications and experience) in machine learning or AI/ computer science with substantial machine learning component
7. Proven hands-on industry experience (minimum 2 years, not including internships) in designing, developing, and deploying machine learning solutions in production environments.
8. Advanced programming skills in languages such as Python with a strong focus on code optimisation, modular design, and efficiency.
9. Deep expertise in developing, training, and deploying models using frameworks like PyTorch and TensorFlow.
10. Demonstrated experience in building scalable, production-grade AI services and automated data pipelines with tools like Docker, Kubernetes, and cloud platforms (e.g., AWS).
11. Strong understanding of data analysis, model evaluation, and error analysis to drive continuous model improvement.
12. Proven ability to collaborate effectively in Agile/ Scrum teams and contribute to cross-functional projects.
13. Exceptional communication skills for articulating complex technical concepts to both technical and non-technical stakeholders.
14. Demonstrated commitment to continuous learning, staying current with state-of-the-art research and applying emerging AI techniques to solve business problems.
Desirable:
15. PhD or equivalent qualification and experience in Machine learning or AI/ Computer Science
16. Experience in applying Natural Language Processing and/ or Speech Technology techniques to solve real-world problems.
17. Experience applying machine learning to educational assessment and learning solutions.
18. Hands-on experience with Large Language Models (LLMs) or foundation models, including fine-tuning and adapting models for specific, production-level applications.
19. Contributions to patents or peer-reviewed research publications in machine learning or related AI fields.
If you would like to know more about the above opportunities and what will make you successful, please see the full job descriptions attached to the bottom of this vacancy on our careers site.
Rewards and benefits
We will support you to be at your best in work and to live well outside of it. In addition to competitive salaries, we offer a world-class, flexible rewards package, featuring family-friendly and planet-friendly benefits including:
20. 28 days annual leave plus bank holidays
21. Private medical and Permanent Health Insurance
22. Discretionary annual bonus
23. Group personal pension scheme
24. Life assurance up to 4 x annual salary
25. Green travel schemes
We are a hybrid working organisation, and we offer a range of flexible working options from day one. We expect most hybrid-working colleagues to spend 40-60% of their time at their dedicated office or location. We will also consider other work arrangements if you wish to work more flexibly or require adjustments due to a disability.
Ready to pursue your potential? Apply now.
We review applications on an ongoing basis, with a closing date for all applications being 28th September, although we may close it earlier if suitable candidates are identified. Interviews are scheduled to take place as deemed appropriate before or after the closing date.
Please note that successful applicants will be subject to satisfactory background checks including DBS due to working in a regulated industry.
Cambridge University Press & Assessment is an approved UK employer for the sponsorship of eligible roles and applicants under the Skilled Worker visa route. Please refer to the gov.uk website for guidance to understand your own eligibility based on the role you are applying for.
Why join us
Joining us is your opportunity to pursue potential. You'll belong to a collaborative team that's exploring new and better ways to serve students, teachers and researchers across the globe - for the benefit of individuals, society and the world. Sharing our mission will inspire your own growth, development and progress, in an environment which embraces difference, change and aspiration.
Cambridge University Press & Assessment is committed to being a place where anyone can enjoy a successful career, where it's safe to speak up, and where we learn continuously to improve together. We welcome applications from all candidates, regardless of demographic characteristics (age, disability, educational attainment, ethnicity, gender, marital status, neurodiversity, religion, sex, gender identity and sexual identity), cultural, or social class/ background.
We believe better outcomes come through diversity of thought, background and approach. We welcome applications from people from all backgrounds and communities, actively seeking to employ people from a wide range of different communities.