Did you know that global spending on AI is estimated to reach $110 billion by 2024? This data makes it clear that AI researchers are going to be the creators of the future technology.
These individuals work on machine learning, data analysis, and algorithm development for a brighter, more advanced technological future. They are found in various domains, from academic institutions and technology companies to government research laboratories.
Interested in this evolving and rewarding career? Read the article to learn everything you need to know about AI researchers.
What is an AI researcher?
An AI researcher is a professional who focuses on understanding and developing the technologies that power artificial intelligence and machine learning. They work to solve complex problems and create new technologies that mimic human intelligence.
They perform different responsibilities depending on the needs of their job. Some may focus on creating new algorithms to make machines learn better, while others may analyse large datasets to find patterns that can be applied to AI.
Many researchers also focus on publishing their findings in scientific journals, contributing to the knowledge of the community.
AI researchers work in different places, such as universities, research institutes, tech companies, and consulting firms. They may also work as educators in academic settings, teaching courses and mentoring future AI professionals.
What does an AI researcher do?
AI researchers may perform the following roles:
Algorithm development
AI researchers create algorithms to handle different problems. For this, they understand the problem, choose the right techniques to solve it, and then program the algorithm. Their goal is to improve the ability of machine to make accurate predictions or decisions.
Model building
Researchers design models that can predict outcomes. They integrate the developed algorithm into a complete machine learning model.
After building the model, they evaluate its performance using different metrics to ensure that it works adequately. They may optimise its performance or remove bugs when the need arises.
Data analysis
Before building a model, they explore the available data to find patterns and transform it. They use statistical methods to understand the data’s structures. This helps them make informed decisions about the type of model they want to build and the features they want to use.
Experiment design
They plan and conduct experiments to evaluate different approaches and hypotheses. It involves writing code to implement algorithms and perform tests. Good experiment design ensures that the results are reliable and can lead to actionable insights.
Collaboration
Researchers often work with other experts in fields like data science, engineering, and ethics. Their collaborative efforts help produce better solutions and speed up the research process. They share responsibilities, learn from each other, and combine their expertise to tackle complex problems.
Literature review
Before starting a research project, AI researchers read existing literature related to the project. This helps them understand what has already been done and how they can contribute.
Publications
Researchers write papers to publish their methods, results, and conclusions. These papers undergo peer review and get published in scientific journals. Publications help the researcher provide valuable information to the scientific community.
Technical documentation
Writing technical documents is an important part of AI research. This includes not just research papers but also documentation that explains how algorithms work and how to use them. This is essential for those who want to further develop the researcher’s work.
Teaching
In academic settings, AI researchers often teach courses related to their field. This could be a course in machine learning or a seminar. Teaching allows them to share knowledge, inspire the next generation, and improve their understanding of the subject.
Grant writing
Research often requires funding. AI researchers write detailed proposals explaining their research objectives, methods, and budget. These proposals are submitted to funding agencies. They evaluate the proposal and may accept it to support the researcher financially if it meets their criteria.
What skills do AI researchers have?
AI researchers possess multiple skills, including:
- Machine learning: They have a deep understanding of machine learning algorithms and tools like PyTorch that offer pre-built functions to speed up the process of machine learning model development. Familiarity with these tools helps them improve their effectiveness.
- Programming: They are familiar with programming languages like Python, R, or Java that they use to design algorithms and models. They allow them to turn their insights into practical applications.
- NLP: AI researchers may sometimes work on projects related to human languages. Here, their natural language processing skills, like sentiment analysis, text summarisation, and language modelling, come in handy.
- Data analysis: They deal with a variety of data for different projects. Hence, knowing how to process, refine and transform data is essential. AI researchers know how to clean data to remove inaccuracies, handle missing values, and convert data into formats that are more suitable for analysis.
- Statistics and mathematics: They have a strong understanding of maths and stats concepts like probability, linear algebra, and calculus. They help them with data analysis and algorithm development.
- Experiment design: They know how to design, run, and interpret experiments to test their hypotheses or theories in a scientific manner. It helps them ensure that the research findings are reliable and the research work is also reproducible.
- Research skills: They have exceptional research skills that they use to learn about the latest findings and stay updated. They conduct literature reviews and understand research papers. These skills also help them write papers and become aware of the requirements of different international journals.
- Project management: Good project management skills allow AI researchers to complete complex projects on time. It helps them keep track of all steps, make efficient use of resources, and lead their teams to get successful results.
- Problem-solving: AI research often involves tackling new challenges that do not have known solutions. Strong problem-solving skills allow AI researchers to think critically and find effective solutions on time.
How to become an AI researcher?
The first step is getting an undergraduate degree in computer science, data science, or a related field. Make sure to take mathematics, programming, and basic machine learning courses to understand their important concepts as well.
A master’s or doctorate degree in AI or related fields can offer more in-depth knowledge.
Earn certifications in specific AI technologies and methodologies. They will help you improve your resume and skillset.
Establish professional relationships with people interested in AI. For this, you can attend conferences and workshops. You can also join online forums and communities.
Gain hands-on experience through internships, entry-level positions and research projects.
Build a strong portfolio to show your skills to future employers or educational institutions.
AI researcher salary in the US
According to Glassdoor data, the annual salary for AI researchers ranges from $88,000 to $152,000 in the US. The average salary is around $115,424 per year. However, it can vary depending on location, job level, experience, etc.
AI researcher job requirements
To get a job as an AI researcher, certain qualifications are typically required, such as:
- AI-related education background
- Technical skills (as mentioned above)
- Soft skills (as mentioned above)
- Research experience
- Industry experience
- Portfolio
Top AI researchers you should know
There are many famous AI engineers in the world, including:
- Fei-Fei Li: She is a computer scientist and computer science professor at Stanford University. She is known for her work in computer vision and cognitive neuroscience. She is the founder of the non-profit organisation AI4ALL.
- Andrew Ng: He is the founder of the “Google Brain” project, cofounder of Coursera, and CEO of Landing.AI.com. He is known for his AI-related online courses.
- Geoffrey Hinton: He is a cognitive psychologist and computer scientist known for his contributions to artificial neural networks. He is known by many as the “Godfather of Deep Learning.”
AI researcher vs data scientist
While both roles involve working with data and algorithms, they differ from each other in many ways.
AI Researchers mainly work in the field of AI through new algorithms and models. On the other hand, data scientists focus more on extracting insights and predictions from data for businesses.
Data scientists spend much time cleaning and preparing data, whereas AI researchers focus more on algorithm development and theoretical work.
AI researcher interview questions
Here are some common questions interviewers ask potential AI researchers to determine whether they are suitable for the job or not.
- What is the difference between supervised and unsupervised learning?
- What are the different types of machine learning algorithms, and when would you use each?
- Describe a challenging problem you have encountered in a previous research project and how you solved it.
- How would you evaluate the performance of a machine learning model?
- What are some ethical concerns related to AI and machine learning?
- How would you address the issue of data privacy in AI research?
Summary
A career as an AI researcher offers many advantages. By acquiring the right skill set and gaining practical experience, you can join this field and play your role in shaping the future of technology. However, remember that this field is continuously evolving. Hence, it is important to keep learning to stay relevant and successful.