Software Engineer Apprentice
Role Overview
This full-time apprenticeship is an advanced, hands-on training programme for people interested in artificial intelligence and machine learning.
The apprentice works alongside AI engineers, data scientists, and product teams on real-world AI solutions.
The role supports data pipelines, machine learning models, and prototype applications.
Key Skills for This Role
Full Job Posting
Job purpose
This full-time apprenticeship is an advanced, hands-on training programme for people interested in artificial intelligence and machine learning.
The apprentice works alongside AI engineers, data scientists, and product teams on real-world AI solutions.
The role supports data pipelines, machine learning models, and prototype applications.
Position details
- The position is based in Maidenhead, United Kingdom.
- The role is full-time.
- The stated experience level is zero to two years.
Model and data pipeline development
- Collect, clean, validate, and prepare data for training and evaluation.
- Support the design, development, and tuning of machine learning and deep learning models.
- Contribute to scalable and reusable data pipelines using modern machine learning workflows.
Experimentation and evaluation
- Conduct experiments and benchmarking exercises to test model performance.
- Perform error analysis, feature importance analysis, and other model diagnostics.
- Track training and testing outcomes to support reproducibility and model versioning.
Engineering contributions
- Build and integrate AI-powered APIs, scripts, and microservices.
- Collaborate on backend services and model deployment in development and test environments.
- Use Git, CI/CD tools, and Docker to maintain codebase quality.
Applied AI domains
- Work on projects involving Natural Language Processing, Computer Vision, Generative AI, or Recommendation Systems.
- Support annotation, feature engineering, and data augmentation tasks where necessary.
Documentation and collaboration
- Write documentation for code, models, datasets, and project workflows.
- Participate in team meetings, sprint planning, and code reviews.
- Engage with mentors to reflect on progress, set learning goals, and track outcomes.
Required qualifications
- Completed Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Mathematics, Software Engineering, or a related STEM field.
- Programming proficiency in Python and common machine learning libraries such as Pandas, NumPy, and Scikit-learn.
- Knowledge of TensorFlow, PyTorch, or a similar machine learning framework.
- Experience with Jupyter Notebooks and version control using Git or GitHub.
- Basic understanding of supervised or unsupervised learning, neural networks, or clustering.
- Ability to interpret data trends, visualize outputs, and debug model behaviour.
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