Deep Learning is a subset of Deep Learning focused on artificial neural networks built on algorithms inspired by the function and structure of the brain. There is a large range of industries that utilize 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 Deep Learning Engineer
• Deep Learning Analyst
• Deep Learning Developer
• Deep Learning Engineer
• Deep Learning Researcher
• Deep Learning Specialist
• NLP & Deep Learning Scientist
• NLP Software Engineer
• Research Scientist – Deep Learning
• Research Scientist – Image Analysis
• Senior Computer Vision Researcher

Graduate Deep Learning Researcher
Deep Learning Engineer

We’ve outlined the latest salary benchmarks for Deep Learning roles in the guides below:

Data, Insight and Analytics Salary Guide

Data, Insight and Analytics Day Rate Guide

Data, Insight and Analytics Within Data Engineering Development Salary Guide

Data, Insight and Analytics Within Data Science Salary Guide

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.

Deep Learning skills: Supervised Learning | Unsupervised Learning | Input Layer | Hidden Layers | Output layer |  Neural Networks | Convolutional Neural Networks (CNN) | Recurrent Neural Networks (RNN) | Long/Short Term Memory (LSTM) | Markov Chain (MC) | Deep Convolutional Network (DCN).

There is a huge range of courses online that all you to improve your 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: £30k – £40k
What They Do:
Supports the development of AI and deep learning models, assists in data preprocessing, and implements small-scale machine learning solutions.

Skills Needed:

• Proficiency in Python and ML libraries (TensorFlow, PyTorch, Keras)
• Basic understanding of neural networks and deep learning concepts
• Familiarity with data wrangling and preprocessing
• Version control (Git) and software engineering best practices
• Ability to evaluate model performance using metrics

Salary: £40k – £55k
What They Do:
Designs and trains deep learning models, experiments with architectures, and collaborates with data scientists and engineers to deploy models into production.

Skills Needed:

• Strong knowledge of CNNs, RNNs, transformers, and other deep learning models
• Experience with large datasets and data pipelines
• Hyperparameter tuning and model optimisation
• Cloud ML platforms (AWS Sagemaker, Azure ML, GCP AI)
• Familiarity with MLOps tools for deployment and monitoring

Salary: £55k – £75k
What They Do:
Leads the design and implementation of advanced deep learning solutions, explores cutting-edge research, and mentors junior engineers.

Skills Needed:

• Advanced neural network architectures (GANs, graph networks, large language models)
• Research and implementation of novel deep learning algorithms
• Optimisation for distributed and GPU computing
• Strong collaboration with product and research teams
• Publications or contributions to open-source projects

Salary: £75k – £95k
What They Do:
Manages deep learning projects and teams, sets technical direction, and ensures scalable AI solutions are deployed across the organisation.

Skills Needed:

• Leadership and team management
• AI strategy and roadmap development
• Expertise in MLOps and CI/CD for AI systems
• Vendor and technology partner evaluation
• Driving innovation and research into production systems

Salary: £95k – £120k
What They Do:
Leads the company’s deep learning strategy, builds high-performing AI teams, and drives enterprise adoption of advanced machine learning solutions.

Skills Needed:

• Department-level strategy and leadership
• Scaling AI and deep learning capabilities
• Strong commercial awareness and enterprise alignment
• Budget and resource planning
• C-suite stakeholder engagement

Salary: £120k – £160k+
What They Do:
Owns the enterprise-wide AI vision, ensures deep learning capabilities deliver transformative business value, and drives innovation through AI.

Skills Needed:

• Executive-level leadership and AI strategy
• Building global AI teams and research functions
• Expertise in AI governance, ethics, and regulation
• C-suite collaboration and influence
• Investment planning for AI platforms and technologies