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Artificial intelligence (AI) researcher
Artificial intelligence (AI) researchers conceive, design and implement algorithms and models which enable machines to exhibit human-level intelligence.
Also known as:
- AI analyst
- AI data specialist
Work activities
AI, or artificial intelligence, refers to the development of computer systems capable of performing tasks that typically require human intelligence, such as learning from data, reasoning and making decisions. Artificial intelligence (AI) researchers explore new frontiers in AI by conceiving, designing, and implementing algorithms and models that enable machines to exhibit this level of intelligence. This involves working in different fields of AI, such as machine learning, natural language processing, computer vision and robotics, to tackle diverse challenges and unlock new possibilities.
A key aspect of an AI researcher's job is to evaluate the performance of AI algorithms and systems. This involves working with large datasets, designing experiments, and fine-tuning parameters. Through iterative refinement and validation, researchers aim to achieve breakthroughs with real-world applications in fields ranging from healthcare and finance to transportation and entertainment.
AI researchers also consider the ethical and societal implications of intelligent systems. They must navigate complex issues such as algorithmic bias, privacy concerns, and the potential impact of AI on employment and society. By engaging with different aspects of society, including ethicists, policymakers, industry leaders and the general public, AI researchers seek to ensure that technological developments are socially responsible and ethical, as well as minimising risks associated with artificial intelligence.
Personal qualities and skills
AI researchers need a broad range of qualities, including advanced technical skills, the ability to consider ethics within a technological context and the soft skills needed to work with others, including non-technical collaborators.
- Strong foundation in computer science, mathematics, and statistics.
- Proficiency in programming languages such as Python, C++, or Java.
- Expertise in machine learning, deep learning, and other AI techniques.
- Ability to analyse complex problems and devise innovative solutions.
- Strong problem-solving and critical thinking skills.
- Excellent communication and collaboration abilities, including the ability to work with non-technical colleagues and stakeholders.
- Attention to detail and ability to work with large datasets.
- Adaptability and willingness to learn new concepts and technologies.
- Ethical mindset and consideration for societal implications of AI.
- Persistence and dedication to overcoming challenges and pushing the boundaries of AI.
Pay and opportunities
Salaries seem to vary dramatically, with data from the jobs site Glassdoor suggesting pay can range between £39,000 and £71,000 for a qualified AI researcher.
AI researchers tend to work a typical full-time week, Monday to Friday. It’s possible you will be expected to work extra hours when approaching a client deadline.
Opportunities tend to be in the private sector, working for small to medium tech start-ups or large tech companies such as Amazon, Google and Microsoft. Opportunities are available throughout the UK but tend to be centred on larger cities such as London, Bristol, Manchester, Cambridge and Birmingham.
Where are vacancies advertised
Vacancies are advertised on national and global jobs boards, sites like LinkedIn, industry websites such as Dice, and on the Government’s Find a Job service.
Entry routes and training
You can qualify for this role by studying towards a university degree or by completing a relevant apprenticeship.
Degree programmes include titles such as:
- Artificial intelligence
- Computer science
- Robotics, autonomous and interactive systems
If you’d prefer to learn on the job by going down the apprenticeship route, there is a level 7 higher apprenticeship in the role of artificial intelligence (AI) data specialist. This leads to level 7 non-degree qualification (equivalent to a master’s degree). You will train with an employer while undertaking study towards your qualification, most likely on block release.
Qualifications
To enter university in a subject such as computer since, you’ll need:
- Two or three A-levels. You will most likely need at least one STEM subject – for example, computing or maths.
- GCSEs in English, maths and potentially other subjects as well. Science subjects will stand you in good stead.
To get onto a level 7 apprenticeship, you’ll need two relevant A-levels. This could include subjects such as computing. You’ll also need GCSEs in English and maths, and potentially other subjects.
Adult opportunities
Age limits: It is illegal for any organisation to set age limits for entry to employment, education or training, unless they can show there is a real need to have these limits.
If you don’t have the qualifications needed to enter a degree, foundation degree or HND course, you might be able to start one after completing an Access course, for example, Access to Computer Science. You don’t usually need any qualifications to enter an Access course, although you should check this with the course provider. A foundation year before the start of a science degree or HND is available at some universities and higher education colleges for students who don’t have the A-levels usually needed for entry.
