Graduate Machine Learning Engineer (Psychometrics & AI)
Role details
Job location
Tech stack
Job description
Immediate start - shape the future of career guidance through data and psychological insight
A rare opportunity to launch your machine learning career with real impact - building AI-driven solutions grounded in psychological theory and evidence. You'll join a team combining psychometric science and machine learning to design tools that support job recruitment, staff development, and career guidance at scale.
Why this role is exciting
For over 15 years, Intalo Group and The Career Network have built innovative career and talent solutions. As we scale our impact, we need a machine learning engineer who can think across disciplines - psychology, education, and AI - to help us move from data patterns to meaningful human insight.
This isn't a "run models" role. It's about asking the right questions: what is being measured, why it matters, and how algorithms can enhance rather than replace human judgment. You'll learn from experienced psychometricians and engineers, sharpen your analytical and conceptual skills, and help build the next generation of evidence-based career tools.
What you'll do
Working within a high-performing product and data team, you'll:
- Analyse complex datasets from psychological and behavioural assessments to uncover interpretable patterns
- Develop and evaluate machine-learning models with attention to psychometric reliability, validity, fairness and appropriate comparison groups
- Collaborate with psychometricians to design scalable assessments that retain psychological meaning
- Create compelling visualisations and reports that link data science outputs to human psychology and decision-making
- Contribute to projects that integrate assessment science with technology at scale
- Support the ethical and responsible use of AI in education, recruitment, and career development
Requirements
Do you have a Master's degree?, * Master's degree in Data Science, Computer Science, Psychology, Cognitive Science, Statistics, or a related quantitative field
- Demonstrated interest in human behaviour, measurement, or applied psychology
- Strong analytical and problem-solving skills with attention to conceptual clarity as well as code quality
- Clear written and verbal communication for both technical and non-technical audiences
- Ability to learn and adapt quickly to new AI tools and theories of human potential
Preferred:
- Familiarity with psychometrics, latent variable modelling, or survey data
- Proficiency in Python (pandas, NumPy, scikit-learn)
- Understanding of machine-learning principles and their limits when applied to psychological constructs
- Experience with data visualisation (Plotly, Power BI, Tableau)
- Knowledge of statistics and experimental design (A/B testing, sampling, validation)
Bonus points for:
- Experience in educational or occupational assessment projects
- Familiarity with R or structural equation modelling tools (lavaan, Mplus)
- Awareness of fairness, bias, and interpretability in AI models
- Interest in the intersection of AI, psychology, ethics, and human development