Machine Learning Research Engineer

Overview

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.

This position has been classified as a hybrid role, requiring the selected candidate to typically spend 40-60% of their time collaborating and connecting face-to-face at their dedicated location. Aside from our hybrid principles, other flexible working requests will be considered from the first day of employment, including other work arrangements should you require adjustments due to a disability or long-term health condition.

We are a Disability Confident (DC) employer that is committed to equality and inclusion ensuring our recruitment process is accessible to all.

• Develop, deploy, and maintain scalable AI-powered solutions for Cambridge English products.
• Optimize and modularize models for reusability and performance.
• Collaborate with product, validation, and business teams to transform capabilities into impactful product features.
• Stay at the forefront of AI and machine learning trends to position Cambridge as a leader in AI-driven assessment and learning.
• Plan, prioritize, and manage own tasks aligned with business objectives.

• Master's degree (or equivalent qualifications and experience) in machine learning or AI/computer science with substantial machine learning component
• Proven hands-on industry experience (minimum 2 years, not including internships) in designing, developing, and deploying machine learning solutions in production environments.
• Advanced programming skills in languages such as Python with a strong focus on code optimization, modular design, and efficiency.
• Deep expertise in developing, training, and deploying models using frameworks like PyTorch and Tensor Flow.
• Demonstrated experience in building scalable, production-grade AI services and automated data pipelines with tools like Docker, Kubernetes, and cloud platforms (e.g., AWS).
• Strong understanding of data analysis, model evaluation, and error analysis to drive continuous model improvement.
• Proven ability to collaborate effectively in Agile/Scrum teams and contribute to cross-functional projects.
• Exceptional communication skills for articulating complex technical concepts to both technical and non-technical stakeholders.
• Demonstrated commitment to continuous learning, staying current with state-of-the-art research and applying emerging AI techniques to solve business problems.

• PhD or equivalent qualification and experience in Machine learning or AI/Computer Science
• Experience in applying Natural Language Processing and/or Speech Technology techniques to solve real-world problems.
• Experience applying machine learning to educational assessment and learning solutions.
• Hands-on experience with Large Language Models (LLMs) or foundation models, including fine-tuning and adapting models for specific, production-level applications.
• Contributions to patents or peer-reviewed research publications in machine learning or related AI fields.

Cambridge University Press & Assessment is a world-leading academic publisher and assessment organisation and a proud part of the University of Cambridge. Shape the future of AI-powered learning solutions with us. We welcome applications from all candidates, regardless of demographic characteristics, and we embrace difference, change and aspiration. We believe better outcomes come through diversity of thought, background and approach.

• 28 days annual leave plus bank holidays
• Private medical and Permanent Health Insurance
• Discretionary annual bonus
• Group personal pension scheme
• Life assurance up to 4 x annual salary
• Green travel schemes