Machine Learning Engineer for Educational Assessment (EdTech)

TL;DR

Machine Learning Engineer (EdTech): Developing and productionizing AI capabilities for educational assessment, such as automated marking and adaptive testing, with an accent on the full ML lifecycle from research to deployment. Focus on designing robust models, evaluating fairness and bias, and integrating prototypes into reliable assessment products.

Location: Hybrid - two days per week in the office in Manchester or Milton Keynes

Salary: £34,000 - £38,400

Company

The largest provider of academic qualifications in the UK, focused on advancing education through AI and assessment innovation.

What you will do

• Design and refine ML models for automated marking, feedback generation, and adaptive testing.
• Evaluate model performance focusing on accuracy, fairness, bias, and alignment with human marking standards.
• Collaborate with AI researchers, developers, and psychometricians to move prototypes into production.
• Develop scalable pipelines for data processing, training, validation, and deployment.
• Identify and mitigate risks related to bias and misuse in high-stakes AI systems.
• Document model architectures and communicate findings to technical and non-technical stakeholders.

Requirements

• Strong Python skills with practical experience using NumPy, Pandas, and scikit-learn.
• Practical experience with PyTorch or TensorFlow.
• Foundational knowledge of supervised learning and the ML lifecycle.
• Bachelor’s or Master’s degree in Computer Science, ML, Data Science, or equivalent experience.
• Ability to explain technical ideas clearly to colleagues across different disciplines.

Nice to have

• NLP knowledge and experience with Hugging Face Transformers or spaCy.
• Experience building end-to-end machine learning systems including deployment.
• Familiarity with software engineering practices such as version control, testing, and CI/CD.
• Knowledge of psychometric models like IRT or computerized adaptive testing (CAT).

Culture & Benefits

• 35-hour working week with flexible, hybrid working arrangements.
• 25 days’ annual leave (rising to 30) plus Christmas closure days.
• Excellent pension scheme with up to 11.5% employer contribution.
• Opportunity to work in an in-house AI lab combining research and production engineering.

Hiring process

• Stage 1: 30-minute Teams interview discussing a shared ML project or GitHub repository.
• Stage 2: Face-to-face interview in Manchester or Milton Keynes focusing on experience and motivation.