Software Engineer Apprentice

VE3; Maidenhead; Hybrid; GBP 20,000 - 30,000; Full time

Job summary

A leading tech company is seeking a Software Engineer Apprentice to engage in an AI Engineer Apprenticeship. This hands-on role allows you to work with experienced professionals in developing machine learning models, data pipelines, and AI applications. Candidates should have a degree in relevant fields and possess programming skills in Python along with familiarity with ML libraries. This hybrid position is based in Maidenhead and encourages collaboration and learning within a supportive environment.

Qualifications

• Bachelor’s or Master’s degree in relevant fields.
• Proficiency in Python and experience with ML libraries.
• Ability to interpret and visualize data trends.

Responsibilities

• Assist in developing data pipelines and machine learning models.
• Conduct experiments to test model performance.
• Help build AI-powered APIs and collaborate on backend services.

Skills

Programming proficiency in Python

Familiarity with common ML libraries (Pandas, NumPy, Scikit-learn)

Experience with TensorFlow or PyTorch

Experience with Jupyter Notebooks

Understanding of supervised/unsupervised learning

Education

Bachelor’s or Master’s degree in Computer Science

Bachelor’s or Master’s degree in Artificial Intelligence

Bachelor’s or Master’s degree in Data Science

Bachelor’s or Master’s degree in Mathematics

Bachelor’s or Master’s degree in Software Engineering

Tools

Git

Docker

Job description

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.

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