There is a large range of industries that utilise Machine Learning such as; Financial Services, Healthcare, Government, Marketing and Sales, Oil and Gas and Transport.

• Algorithm Researcher

• Computer Vision Engineer

• Computer Vision Expert

• Computer Vision Scientist

• Computer Vision Software Engineer

• Graduate Machine Learning Engineer

• Machine Learning Analyst

• Machine Learning Developer

• Machine Learning Engineer

• Machine Learning Researcher

• Machine Learning Specialist

• ML Engineer

• ML Engineer (duplicate – listed twice)

• ML Software Engineer

• ML Specialist

• NLP & Deep Learning Scientist

• NLP Software Engineer

• Research Scientist – Deep Learning

• Research Scientist – ML & Image Analysis

• Senior Computer Vision Researcher

• Deep Learning Researcher

• Graduate Machine Learning Researcher
• Machine Learning Engineer
• Senior ML Engineer
• Head of ML (or similar)

At an entry level, junior / graduate Machine Learning professionals on average will be earning between £30k-£35k. At the mid-level you’d be looking to earn £50k-£60k and seniors would be looking to earn £70k+.

The skills needed can be split into 3 categories; fundamental skills, programming skills and machine learning languages.

Fundamental skills: Probability – using techniques like Markov Decision Processes and Bayes Nets | Statistics – being able to analyse variance and test hypotheses | Data Modelling – understanding the structure of datasets, spotting gaps and filling them with data.

Programming skills: Fundamentals – Data Structures | Algorithms | Computer Architecture | b-trees | Sort Algos and Stacks | Software Design – A background in APIs e.g. web APIs and static/dynamic libraries | ML Libraries – e.g. TensorFlow, CNTK, MLib.

Machine Learning languages: C/C++ – e;g; LibSVM, Shark and mlpack | R | Python – NumPy, SciPy Pandas, scikit-learn, Theano and TensorFlow.

There are a huge range of courses online that all help to improve skills in these areas such as; Coursera, Udacity and Kaggle.

A Masters (MSc) or Doctorate (PhD) in a maths, physics, statistics, artificial intelligence (AI), software engineering, engineering or computer science field with technical skills in programming. Statistics and probability are key here as well as demonstrable experience working with large data sets and experience using machine learning and statistical methods.

Salary: £28k – £38k
What They Do:
Supports data science and engineering teams by building and testing basic ML models, cleaning data, and contributing to research and development efforts.

Skills Needed:

• Python and ML libraries (scikit-learn, TensorFlow, PyTorch)
• Basic understanding of supervised and unsupervised learning
• Data preprocessing and feature engineering
• Familiarity with Jupyter notebooks and Git
• Strong mathematical foundation (linear algebra, statistics)

Salary: £38k – £50k
What They Do:
Designs, builds, and deploys machine learning models into production systems. Works closely with data scientists and software engineers to integrate ML solutions.

Skills Needed:

• Model training, evaluation, and deployment
• Experience with cloud platforms (AWS, GCP, Azure)
• Version control and CI/CD pipelines
• Understanding of model performance metrics
• Collaboration and communication skills

Salary: £50k – £70k
What They Do:
Leads ML projects, optimises model performance, and contributes to strategic decisions. May specialise in areas like NLP, computer vision, or recommendation systems.

Skills Needed:

• Advanced ML techniques (ensemble methods, deep learning)
• Domain-specific expertise (e.g., NLP, CV, time-series)
• Model interpretability and explainability
• Mentoring junior engineers
• Experiment design and statistical validation

Salary: £70k – £90k
What They Do:
Oversees ML system architecture and team workflows. Ensures scalability, reliability, and ethical use of ML models across products and services.

Skills Needed:

• ML system design and architecture
• Cross-functional leadership and project management
• Data governance and model lifecycle management
• Stakeholder engagement and technical strategy
• Knowledge of MLOps and automation tools

Salary: £90k – £120k
What They Do:
Defines the organisation’s ML strategy, manages teams across multiple projects, and ensures alignment with business goals and ethical standards.

Skills Needed:

• Strategic planning and team scaling
• Budgeting and resource allocation
• Collaboration with product, engineering, and executive teams
• Deep understanding of AI ethics and compliance
• Driving innovation and research partnerships

Salary: £120k – £160k+
What They Do:
Leads enterprise-wide AI initiatives, sets long-term vision, and ensures ML drives competitive advantage and customer value.

Skills Needed:

• Executive leadership and vision-setting
• Global AI strategy and governance
• Commercial acumen and board-level communication
• Building partnerships with academia and industry
• Championing responsible AI and innovation