Machine Learning Engineer for Educational Assessment in Manchester

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.

Salary and location

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).

Diversity and Inclusion Statement

At AQA, we are committed to fostering a workplace that celebrates diversity and promotes equity and inclusion. We believe that a diverse team brings richer perspectives and drives better outcomes. Our ED&I strategy ensures that everyone—regardless of religion, ethnicity, gender identity or expression, age, disability, sexual orientation, or background—is valued, respected, and empowered to thrive. We actively promote inclusive language, avoid stereotypes, and strive for representation across all dimensions of diversity. We welcome applications from individuals of all backgrounds and lived experiences.

Application Process

To apply, please submit your CV through the AQA careers site. Applications close on Sunday 9 August 2026.

Stage 1: a 30-minute Teams interview where you will talk through the shared project or artefact and discuss the technical decisions behind it.

Stage 2: a face-to-face interview in Manchester or Milton Keynes, focused on your wider professional experience, collaboration style and motivation for educational assessment.

Recruitment

We have a preferred supplier list (PSL) in place. Unsolicited CVs will be treated as a gift. We will not be subject to or liable under your terms and conditions for agency fees.

Full Job Description Summary

Accountable to the Head of AI for Assessment Innovation, the overall purpose of this role is to develop models and algorithms as required by new assessment products and services. The post holder will research and develop AI capabilities that can enable new assessment products, increase the breadth of assessment services on offer and help shape long-term tech innovation and solutions. They will ideate and develop proofs of concept and prototypes and ensure they are cutting-edge, relevant and fit-for-purpose.

Research, development and evaluation of AI solutions for assessment are key enablers in a range of diversification, digitisation and customer programmes. The AI for Assessment Innovation team is AQA’s in-house AI for assessment lab, providing services and solutions alongside and in collaboration with contractors and partners.

The team’s responsibilities are:

• Research and development of AI features for new products or as part of contracted services.
• EdTech partnership support through targeted evaluations and testing of third-party AI tools.
• Providing AI for assessment expertise to the whole AQA group and advancing AQA’s knowledge and know-how.

The role sits within the AI for Assessment Innovations team, in the Assessment Research and Innovation business area. Reporting to the Head of AI for Assessment, the role collaborates with a team of AI researchers, developers and managers and will have line management responsibility for AI for Assessment apprentices.

Activities:

• AI model development for assessment: Design, build, and refine machine learning models that support educational assessment use cases, such as automated marking (e.g., essays, short answers), feedback generation and learner support, skill estimation, proficiency modelling, and adaptive testing. Select appropriate modelling approaches (e.g., NLP models, classical ML, or deep learning) based on pedagogical and product requirements. Conduct rigorous experimentation, including hyperparameter tuning and ablation studies, to improve model performance and fairness.
• Educational assessment research: Work with complex educational datasets (e.g., learner responses, interaction logs, assessment outcomes). Design evaluation frameworks that go beyond accuracy to include fairness and bias across learner groups, marking reliability and consistency, alignment with human marking standards and mark schemes. Work closely with psychometricians, assessment experts and product teams to translate educational requirements into technical solutions. Incorporate domain knowledge (e.g., marking schemes, assessment objectives, curriculum standards) into model design.
• From prototype to operationalisation: Develop scalable pipelines for data processing, model training, validation, and deployment. Collaborate and support the teams responsible for integrating models into production systems. Contribute to CI/CD workflows, model versioning, and reproducibility practices.
• Responsible AI and governance: Identify, assess, and mitigate risks related to bias, fairness, and misuse in assessment AI systems. Contribute to the development of explainable and transparent AI systems suitable for high-stakes exams or classroom use. Work with the relevant AQA teams to ensure compliance with relevant regulatory and ethical standards in education.
• Documentation and knowledge sharing: Document model architectures, decisions, evaluation results, and limitations. Communicate findings clearly to both technical and non-technical stakeholders. Contribute to internal best practices, reusable components, and knowledge sharing across teams.

To be successful in this role, you will need to demonstrate:

Essential Motivation: A keen interest in the education or educational assessment sector, and a drive to furthering AQA’s mission.

Machine learning and NLP expertise: Understanding of machine learning techniques, including supervised learning, model evaluation and optimisation. Natural Language Processing (NLP) for text-based assessment and some knowledge of multi-modal models. Experience building end-to-end ML systems from data ingestion to deployment. Familiarity with model interpretability techniques (e.g., SHAP, LIME).

Engineering: Proficient in Python and core ML/data libraries (e.g., PyTorch/TensorFlow, Scikit-learn, Pandas). Knowledge or experience with production systems such as API development, containerisation and cloud platforms. Solid understanding of software engineering practices: version control, testing, modular design.

Research skills: Experience working with real-world datasets, including noisy or incomplete data. Understanding of evaluation methodologies, particularly in contexts where ground truth may be subjective (e.g. human marking).

Analytical and problem-solving skills: Ability to translate ambiguous, domain-specific problems into structured ML solutions. Strong critical thinking when interpreting model outputs in high-stakes contexts. Attention to detail, particularly when working with sensitive learner data and evaluation outcomes.

Communication and Collaboration: Ability to work effectively in multidisciplinary teams. Strong communication skills, including explaining technical concepts to educators and non-technical stakeholders. Experience contributing to collaborative development environments.

Education and Experience: Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field, or equivalent experience. Hands-on experience in machine learning or applied AI, acquired in a range of contexts.

Desirable: Interest in or experience with education technology, assessment systems, or learning analytics. Awareness of concepts relevant to assessment such as reliability and validity, computerised adaptive testing (CAT), Item response theory (IRT) or similar psychometric models. Experience in education, assessment, or a related.

AQA is an independent charity that sets and marks over half of all GCSEs and A-levels in the UK every year. Our purpose is to advance education by helping students and teachers to realise their potential. As part of AQA, you’ll very quickly appreciate the determination and unwavering passion to deliver this goal in everything we do. To help drive these ambitions, AQA invests in the development of its people by offering a range of professional development and learning opportunities leading to over 50% of our permanent roles being filled internally.

Reasonable Adjustments

If you have any requirements for reasonable adjustments in relation to the application, interview or the prospective job, please contact Faye Harrison (she/her) at fharrison@aqa.org.uk or on 07813 724161. We are asking for this information to make the process as equitable as possible for each candidate. Please note that Faye will not be able to assist you with enquiries regarding Temporary vacancies or non-recruitment enquiries. If you have query regarding Temporary vacancies, please contact: temprecruit@aqa.org.uk.

Smart Working

We’re operating a smart working model. This allows for our colleagues to work from two days a week in one of our offices across England.

Equality, diversity and inclusion

AQA is an equal opportunity employer committed to fostering an inclusive and diverse workplace where everyone - regardless of religion, ethnicity, gender identity or expression, age, disability, sexual orientation, or background - is valued, respected, and supported to thrive.

Conflict of Interest

Please note that due to the confidential nature of our work, we are unable to employ people for our temporary roles who are currently a candidate for Key Stage 4 and 5 public examinations.

Safeguarding

AQA is committed to the safeguarding of children and adults at risk. We’re dedicated to reducing the risk of employing or contracting any person intent on abusing their position of trust, along with identifying and responding to any incident of alleged abuse from its employees or associates fairly and swiftly.

For more information on safeguarding at AQA please visit the AQA website here.

Contact

Temporary roles: temprecruit@aqa.org.uk Permanent and Fixed Term roles: opportunities@aqa.org.uk