Becoming an AI developer
Artificial intelligence (AI) is reshaping industries and with it, creating careers that didn’t exist as early as a decade ago. But while AI can do many things, it can't develop itself. Which is why AI developers exist to design smarter systems and solve real-world problems, to support the next generation of intelligence tech.
This guide breaks down what an AI developer does, the skills you’ll need, and how to get started in this exciting field. Whether you’re exploring your options or building on existing experience, it’s all here to help you move forward.
What is an AI developer?
An AI developer is a specialist who designs and builds artificial intelligence systems that solve problems and improve processes. Using machine learning models, programming languages, and AI frameworks, they create applications like chatbots, predictive analytics tools, natural language processing systems, and neural networks.
AI developers play a key role in shaping the future of technology, tackling business challenges, and delivering practical AI solutions for real-world use. Their work combines technical expertise with creativity to make AI systems smarter, faster, and more effective.
What does an AI developer do?
AI developers take part in every step of building artificial intelligence systems. Their work often includes collecting and preparing data, as well as designing, creating and launching AI models. Because of the tasks they're responsible for, the role of an AI developer requires a mix of technical skills, problem-solving abilities, and collaboration with programming and software development team.
The responsibilities of an AI developer often include:
Designing and implementing AI models and machine learning algorithms.
Collaborating with data scientists to understand data structures and perform statistical analysis.
Creating and deploying AI systems using AI frameworks and tools.
Addressing business challenges through AI applications like predictive analytics, speech recognition, and generative AI.
Steps to become an AI developer
Becoming an AI developer might feel like a big goal, but it’s more achievable than you think. Follow the steps below to build the skills, knowledge, and confidence to start a successful AI developer career.
1. Get to know the artificial intelligence developer role
Before jumping in, it’s important to understand what an AI developer actually does. These professionals work on creating smart systems that solve real-world problems – whether that’s using machine learning to improve healthcare, designing predictive tools for finance, or creating new technology in the automotive industry. AI developers combine programming, data analysis, and creativity to make a tangible impact on how things work.
2. Pursue formal education
Most AI developers start with a bachelor’s degree to learn computer science fundamentals, data science or artificial intelligence. On a bachelor's degree, you’ll learn essential skills like programming, data structures, machine learning concepts, and software engineering knowledge.
If you already have some experience in the field, a master’s degree in AI can open doors to senior roles, higher salaries, or even a career shift.
Key areas of study include:
Machine learning concepts and algorithms.
Data structures and statistical analysis.
Programming and software engineering knowledge.
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Learn about programming languages, and master machine learning, AI systems, and data science while developing critical thinking and problem-solving skills.
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Go to MSc Artificial Intelligence3. Learn programming languages and AI technologies
Programming languages are at the heart of AI development. Focus on mastering Python, Java, R, and C++, as these are widely used for building AI applications. Familiarise yourself with AI frameworks like TensorFlow, PyTorch, and Scikit-learn to create AI systems effectively.
4. Gain experience with AI tools and real-world projects
The best way to truly understand AI development is by rolling up your sleeves and working on real-world problems. Gaining hands-on experience with AI tools and projects will help you turn theory into practical skills, making you job-ready and confident in your abilities.
Why real-world projects matter
AI development isn’t just about knowing the theory – it’s about applying your knowledge to create solutions that work in real scenarios. By working on projects, you’ll learn how to:
Train and fine-tune machine learning models to solve specific challenges.
Experiment with neural networks and deep learning concepts to tackle complex problems.
Use AI tools and frameworks to build applications that make a real impact.
Handle the unexpected, like data inconsistencies or model training errors, which are common in AI development.
How to get real-world experience
5. Develop AI development skills and soft skills
In addition to technical skills, soft skills like critical thinking, problem-solving, and communication are important for collaborating with teams and addressing business challenges. These skills can help you work more effectively as an AI developer.
6. Consider certifications to boost your expertise
Certifications can show employers you’re serious about AI development. Many platforms now offer certifications in AI and machine learning, often with hands-on projects included. These can be a great way to enhance your resume or fill in knowledge gaps.
7. Stay updated with industry trends
The AI field is constantly evolving. Keep up with research papers, industry news, and advancements in AI systems, including neural networks, natural language processing, and support vector machines. Staying informed ensures your skills remain relevant in the global AI market.
Skills you need to become an AI developer
To thrive as an AI developer, you’ll need a mix of technical expertise, creative problem-solving, and teamwork abilities. While mastering technical skills is crucial, developing soft skills will make you a well-rounded professional ready to tackle diverse challenges. Let’s break it down:
Technical skills: building a solid foundation in AI
AI development relies heavily on technical know-how. Here are the core skills you’ll need:
Programming skills: Proficiency in Python, Java, R, or C++ is essential. These languages are the backbone of AI applications and machine learning models.
Machine learning and deep learning: Understanding both machine learning concepts and deep learning techniques will help you build and optimise AI systems.
Data analysis and statistical skills: Performing statistical analysis and working with data structures are key to preparing datasets and interpreting results.
AI development knowledge: Learn to use frameworks, such as TensorFlow and PyTorch, to create, train, and deploy AI models effectively.
Data structures and AI algorithms: A strong grasp of these concepts will help you design efficient and reliable AI systems.
Tools to master as an AI developer
To succeed in AI development, you’ll need hands-on experience with the tools and technologies professionals use every day. Here are the key tools to get familiar with:
TensorFlow and PyTorch: You'll need these frameworks to buld and train machine learning and deep learning models.
Scikit-learn: Great for beginners and intermediate users working on tasks like predictive modelling and data pre-processing.
Keras: A high-level API that makes building neural networks straightforward and accessible.
Google Cloud AI tools: These tools allow you to develop, deploy, and scale AI solutions efficiently in real-world settings.
OpenCV: Used for computer vision projects, such as facial recognition and object detection.
Jupyter Notebooks: A great tool for documenting and sharing your AI experiments and projects.
MATLAB: Useful for mathematical computations, simulations, and designing AI algorithms.
Soft skills: making you stand out
While technical abilities get you in the door, soft skills ensure you excel in your career. Developing the skills below will help you navigate the challenges of AI projects and make a lasting impact.
Critical thinking skills: Evaluate challenges, identify the best AI techniques, and make decisions that drive results.
Problem-solving skills: Overcome technical and non-technical obstacles, from debugging code to finding innovative solutions to business challenges.
Collaboration and communication: Explain AI concepts clearly to non-technical stakeholders and work effectively with data scientists, software developers, and project managers.
Career paths for AI developers
The world of AI development is bursting with opportunities, offering roles that span from beginner to expert. Whether you’re just getting started or you dream of leading ground-breaking projects, a career in AI lets you work with cutting-edge technologies that are changing the way we live and work. Here’s what your career path could look like and estimated salaries* for each role.
Entry-level roles
When you’re new to AI development, your focus will be on building skills, getting hands-on experience, and learning how to apply AI to real-world problems. Entry-level roles are the perfect launch pad for your journey.
AI Developer Intern – £42,332: Learn the essentials by supporting experienced developers with tasks like coding AI systems and testing machine learning models.
Junior AI Developer – £41,634: Work on small but impactful projects, such as training AI models or developing simple AI applications.
These roles help you get comfortable with programming, data structures, and AI tools, setting the stage for your next step.
Mid-level roles
Once you’ve got a few years under your belt, you’ll start taking on more responsibility. Mid-level roles let you create AI solutions that tackle real-world challenges while sharpening your technical skills.
Artificial Intelligence Developer – £44,014: Design, build, and deploy AI models that can learn and adapt. You’ll be the go-to person for creating AI systems that make a difference.
Business Intelligence Developer – £44,732: Create data-driven AI solutions to support decision-making and strategic planning.
AI Engineer – £57,202: Tailor AI tools for specific industries like healthcare, finance, or retail, creating systems that solve industry-specific challenges.
Machine Learning Engineer – £65,776: Focus on developing and fine-tuning machine learning algorithms to make AI smarter and faster.
Senior roles
With experience and a proven track record, you’ll find opportunities to lead projects, manage teams, and drive innovation in AI. Senior roles are your chance to make a lasting impact on the future of AI.
AI Architect – £53,420: Design large-scale AI systems, ensuring they’re built to handle big challenges and deliver real results.
AI Product Manager – £60,670: Balance the technical and business sides of AI development, ensuring the solutions you create meet real-world needs.
Chief AI Officer – £68,094: Take charge of an organisation’s AI strategy, leading innovation and driving AI adoption across all areas of the business.
Lead Machine Learning Engineer – £111,848: Oversee a team of engineers working on cutting-edge AI models and algorithms.
Specialised roles
As you gain experience, you may find yourself drawn to specific areas of AI. Here are some exciting specialisations to consider:
Natural Language Processing (NLP) Specialist – £53,167: Build AI that understands and communicates in human language, from chatbots to speech recognition.
Computer Vision Engineer – £53,750: Develop systems that interpret images and videos, like facial recognition or self-driving cars.
Deep Learning Engineer – £57,735: Focus on neural networks to power the next generation of AI innovations.
*Salary information from glassdoor.co.uk and correct as of October 2024.
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Our BSc (Hons) Artificial Intelligence degree is perfect for those starting their journey in AI, covering programming, machine learning, and AI systems, with hands-on projects to build real-world experience.
If you're ready to take your expertise further, our MSc Artificial Intelligence course focuses on advanced topics like deep learning, generative AI, and AI applications, with options to tailor your studies to your career ambitions.
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