Software Engineer Apprentice
Education: Degree or Postgraduate
Location: Hybrid (Maidenhead-based)
Job Purpose
The AI Engineer Apprenticeship is an advanced, hands-on training programme designed for individuals passionate about artificial intelligence and machine learning. This role offers the opportunity to work alongside seasoned AI engineers, data scientists, and product teams, contributing to the development of real-world AI solutions.
You will support the development of data pipelines, machine learning models, and prototype applications .
Requirements
Key Responsibilities
Model & Data Pipeline Development
* Assist in collecting, cleaning, validating, and preparing 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 ML workflows.
Experimentation & Evaluation
* Conduct experiments and benchmarking exercises to test model performance.
* Perform error analysis, feature importance, and other model diagnostics.
* Track and log training/testing outcomes to support reproducibility and model versioning.
Engineering Contributions
* Help build and integrate AI-powered APIs, scripts, and microservices.
* Collaborate on backend services and model deployment in dev/test environments.
* Use Git, CI/CD tools, and containerization (e.g., Docker) to maintain codebase quality.
Applied AI Domains
* Work on projects that involve Natural Language Processing (NLP), Computer Vision, Generative AI, or Recommendation Systems.
* Support annotation, feature engineering, and augmentation tasks where necessary.
Documentation & Collaboration
* Write clear, well-organized 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
A Bachelor’s or Master’s degree (completed) in:
Computer Science
Artificial Intelligence
Data Science
Mathematics
Software Engineering
Core Skills & Competencies
Technical Skills
* Programming proficiency in Python and common ML libraries such as:
* Pandas, NumPy, Scikit-learn
* TensorFlow, PyTorch, or similar
* Experience with Jupyter Notebooks and version control (Git/GitHub)
* Basic understanding of supervised/unsupervised learning, neural networks, or clustering
Analytical Abilities
* Ability to interpret data trends, visualize outputs, and debug model behaviour