AI/ML Engineer

What they do

• Design and train machine learning models (neural networks, decision trees, etc.)
• Process and analyse large datasets for model training
• Deploy ML models into production applications
• Work with frameworks like TensorFlow, PyTorch, and scikit-learn
• Collaborate with data scientists and software engineers

Entry pathways

Ways to get into this role in the UK:

• Degree in Computer Science, Mathematics, Physics, or AI/ML (often MSc for specialisation)
• Software engineering background with self-directed ML learning
• Data Science or AI apprenticeship programmes
• Online courses (Coursera, edX, Fast.ai) plus portfolio projects
• PhD route for research-focused roles

A day in the life

Your morning starts with checking how a machine learning model you deployed last week is performing—the accuracy metrics look promising. You spend the late morning cleaning a large dataset, removing errors and filling gaps, which is often more time-consuming than it sounds. After lunch you run experiments in a Jupyter notebook, tweaking the parameters of a neural network and comparing results. A quick chat with a data scientist colleague sparks a new idea. The afternoon is spent writing up your findings and committing your latest model code to the team's shared repository.