At AQA, we're committed to advancing education and we're committed to our people. As the largest provider of academic qualifications in the UK , we mark over 10 million exam papers each year and it's our people who make this happen.
Machine Learning Engineer (Education Research)
Permanent
Manchester: £34,000 - £36,900 / Milton Keynes: £35,400 - £38,400
Working Arrangements; Hybrid - two days per week in the office
Introduction
AQA is building its AI for assessment capability and is looking for a junior machine learning engineer who wants to apply AI and machine learning to meaningful educational challenges. This is a distinctive early-career opportunity to work across the full applied machine learning lifecycle: researching and testing new approaches, evaluating them rigorously, and helping turn successful prototypes into reliable capabilities that can be deployed within assessment products and services. You will join AQA's in-house AI for assessment lab and work alongside experienced AI researchers, software developers, product teams, psychometricians and assessment experts. You will receive support to develop both your research and engineering skills while contributing to work with real educational purpose.
Purpose of the role
You will contribute to the research, development and productionisation of AI capabilities for educational assessment. These may include automated marking, feedback generation, learner support, skill estimation, proficiency modelling and adaptive testing. The role combines applied research with practical engineering. You will help investigate and validate promising approaches, then work collaboratively with technical and product colleagues to turn successful research into reproducible, maintainable and deployable machine learning capabilities.
Key responsibilities
- Design, develop and refine machine learning models and prototypes that support educational assessment, helping to translate assessment needs into practical AI solutions and providing evidence for future development decisions.
- Evaluate model performance against technical and assessment measures, including accuracy, fairness, bias, reliability and alignment with human marking standards, while ensuring methods and results are clearly documented and reproducible.
- Work collaboratively with AI researchers, developers, psychometricians and product teams to build, deploy and continuously improve machine learning solutions, developing robust engineering practices and end-to-end experience across the full AI lifecycle.
What we are looking for Essential
- Strong Python skills, with practical experience using relevant data and machine learning libraries such as NumPy, Pandas and scikit-learn.
- Practical experience with at least one deep-learning framework, such as PyTorch or TensorFlow.
- A good foundation in machine learning, including supervised learning and model evaluation.
- A good understanding of the machine learning lifecycle, from data ingestion and cleaning through to model development and validation.
- An interest in education or educational assessment and motivation to apply technology in support of AQA's mission.
- Strong communication and collaboration skills, including the ability to explain technical ideas clearly and learn from colleagues across different disciplines.
Desirable
- NLP knowledge or experience relevant to text-based assessment.
- Familiarity with NLP libraries or frameworks such as Hugging Face Transformers or spaCy.
- Experience of, or exposure to, building end-to-end machine learning systems, including deployment.
- Familiarity with software-engineering practices such as version control, testing, code review and technical documentation.
- Exposure to sequential modelling.
- Experience working with multimodal data, including data processing and synchronisation.
What's in it for you
This is an opportunity to build an applied AI career in an environment combining research, engineering and real educational purpose. Unlike many early-career research roles, you will have the opportunity to follow promising work beyond the prototype: learning how models are evaluated, engineered, integrated and deployed within real products and services. You will gain practical experience across the full machine learning lifecycle while working with experienced specialists in AI, software development, product development, psychometrics and educational assessment.
- Contribute to AI capabilities in areas such as automated marking, personalised feedback, item generation and learner support;
- Develop practical experience of both applied ML research and production engineering;
- Learn how responsible AI capabilities are tested, deployed, monitored and improved;
- See how your work contributes to products and services used to address meaningful educational needs.
- A 35-hour working week with flexible, hybrid working
- 25 days' annual leave (rising to 30), plus Christmas closure days
- Excellent pension (up to 11.5% employer contribution) etc