How To Become an AI Developer in 10 Steps

How To Become an AI Developer in 10 Steps

The field of artificial intelligence is continuing to grow and impact various industries. Over the last few years, the world has seen the development of voice assistants like Siri and Alexa and the growth of chatbots like ChatGPT. By 2025, the global AI market could be worth over $190 billion.

As the need for qualified AI developers picks up, the increase in demand should lead to the development of numerous career opportunities. In this article, you’ll gain a better understanding of what an AI developer does and the steps you can take to become one.

What does an AI developer do?

An AI developer is a software engineer specializing in the development of AI systems. They use their programming, machine learning, and data science knowledge to create AI systems to perform tasks that would otherwise need human intervention.

The median pay rate for an AI developer working on a freelance or project basis is between $25 and $50 per hour. According to the Bureau of Labor Statistics (BLS), the need for software developers and quality assurance (QA) analysts is projected to grow by 25% through 2031. The median salary in 2021 was $109,020.

Main responsibilities of an AI developer

An AI developer performs several key functions. We cover what AI developers handle on a regular basis.

  • Addressing business challenges. AI developers work to come up with creative solutions to solve everyday problems through AI integration and implementation.
  • Developing AI systems. AI engineers create AI-based systems using machine learning algorithms, natural language processing (NLP) systems, computer vision systems, deep learning, and other AI methods.
  • Programming and software development. AI developers write code and develop software based on programming languages like Python, Java, and C++. They may also work with frameworks and libraries like TensorFlow, PyTorch, and Scikit-learn.
  • Data analysis and model training. Developers often work with large datasets to develop machine learning models. Some may even use algorithms and statistical techniques to fine-tune models.
  • Staying up to date on emerging technologies. As new products continue to develop and come to market, AI engineers stay current on new tools and emerging methodologies.

Skills needed to become an AI developer

An effective AI developer likely possesses several (if not all) of the following skill sets:

  • Programming and software development knowledge. Since most of your work will involve working with complex technologies, you must be well-versed in programming language and software development processes.
  • Software engineering knowledge. You should have a basic understanding of software engineering and how it plays out in the development of AI models and technologies.
  • Problem-solving and critical thinking. AI developers put their problem-solving and decision-making skills to work as they evaluate existing systems and look for methods of potential improvement.
  • Creativity. The future success of AI depends on engineers’ and developers’ ability to use AI to solve problems. AI engineers should be ready to flex their creative muscles as they find new and valuable ways to use AI.
  • Attention to detail. Since AI systems rely on accuracy, AI programmers should have strong attention to detail to fix bugs and promote better automation.
  • Self-motivation. Solving complex problems using big data and blazing trails in a new industry can be challenging, which is why AI engineers must be self-motivated individuals who enjoy new challenges.
  • Communication skills. Soft skills like communication can help you effectively collaborate with other stakeholders as you work together on projects.

Check out the open jobs currently listed on Upwork to gain experience in software development or web programming.

How to become an artificial intelligence developer

Below, we offer some steps for anyone thinking about becoming an AI developer.

Steps to become an AI developer:

  1. Pursue formal education and training
  2. Learn computer science and programming languages
  3. Master machine learning and deep learning concepts
  4. Develop skills in data science and analytics
  5. Gain hands-on experience with AI projects
  6. Enhance technical skills with frameworks and tools
  7. Develop soft skills for effective collaboration
  8. Stay updated and continuously learn
  9. Build a professional network and showcase your work
  10. Explore career opportunities and apply for AI developer roles

1. Pursue formal education and training

As you take the first steps toward becoming an AI developer, getting a bachelor’s degree or master’s degree in computer science, data science, or a related field is a great way to start.

You can also take advantage of online courses, boot camps, or internships to gain practical experience, including:

  • Brainstation. Brainstation offers industry-leading tech and coding courses to equip learners with new software engineering and UX design skills.
  • Great Learning. Great Learning partners with top universities from across the country, such as Stanford Business School and the McCombs School of Business at the University of Texas in Austin.
  • Metis. Metis partners with universities to provide data science and analytics training for individuals, companies, and institutions. They hope to educate people on how to find value through data analysis.

Pursue your interests both inside and outside the classroom. Some people achieve success in the field of AI development without a relevant degree by building on the work they’ve done outside of school.

2. Learn computer science and programming languages

Once you start working in AI development, a thorough knowledge of computer science and programming language is essential. Take time to study computer science fundamentals, algorithms, and data structures. You should also gain proficiency in programming languages like Python, Java, and C++.

3. Master machine learning and deep learning concepts

Understanding machine learning algorithms, regression, and classification can help position you for success in your future career as an AI engineer. To get ready for the work you’ll do, set aside some time to dive into deep learning techniques, neural networks, and convolutional neural networks (CNNs).

4. Develop skills in data science and analytics

AI developers work with data science and analytics on a regular basis. With this in mind, you should learn data preprocessing, feature engineering, and data visualization as you build your skills. You can also gain expertise by working with datasets and performing statistical analysis.

5. Gain hands-on experience with AI projects

Once you have a solid foundation, you can start putting your skills to the test by working on actual AI projects. Try your hand at building machine learning models and AI applications. See if you can collaborate with stakeholders and other professionals to understand real-world requirements and implementations of AI technologies.

6. Enhance technical skills with frameworks and tools

Once you begin working in AI, you may have opportunities to use popular AI frameworks like TensorFlow, PyTorch, or Scikit-learn. Before you advance too much further in your training or career, become familiar with how these tools work and what they can do. You should also explore application programming interfaces (APIs) and libraries that facilitate AI development and deployment.

7. Develop soft skills for effective collaboration

As an AI developer, you won’t work in isolation. You’ll team up with other stakeholders and team members on group projects and collaborative efforts. Ensure these projects run as smoothly and effectively as possible by honing your communication and teamwork skills. Look for ways to improve your problem-solving and critical-thinking abilities in a way that helps you tackle complex AI challenges.

8. Stay updated and continuously learn

Like any emerging field, the AI industry is constantly developing and growing. Stay current about advancements and trends within the world of AI. You can keep up with what’s going on by reading research papers and engaging in conversations with other AI developers.

It might be worth your time to engage with online workshops and tutorials taught by expert AI engineers. A wide range of online resources can be helpful for continuing education and development.

Perhaps you might decide to earn a new certification to further your career and stand out from the crowd. Some popular options you may want to consider include:

  • Certified Artificial Intelligence Engineer (CAIE). This course is offered by the U.S. Artificial Intelligence Institute and covers several relevant topics. The self-paced program takes between eight and 10 hours per week for one to six months.
  • CertNexus’ Certified AI Practitioner. This intermediate-level class covers ethics, data structure, process management, and machine learning algorithms. Knowledge of basic AI concepts and some database or programming experience is helpful.
  • Google Data Analytics Certificate. Google and Coursera partnered to create this online analytics course. For less than 10 hours per week, you’ll learn basic information about data types and structures, data storytelling, and R programming in a way that helps you build complex computer systems and analyze large portions of data.

Finally, ensure you’re regularly using AI tools so you can maintain a clear understanding of user needs, experiences, and interfaces. This helps ensure you continue to create useful products that provide value to your customers.

9. Build a professional network and showcase your work

Trying to find a job can be challenging, but networking with professionals in your field who may know about open positions can help. Develop your LinkedIn presence and connect with others in your field.

Consider building a portfolio or GitHub repository to show off projects you’ve worked on in the past. You can share this portfolio along with your resume to highlight your skills and past experiences.

10. Explore career opportunities and apply for AI developer roles

Research career opportunities in AI development, data science, or machine learning engineering. This will give you an idea of what jobs might be available and what keywords you can use as you search for open positions.

As you apply for jobs, prepare for interviews by practicing technical interview questions and showcasing your hands-on experience. Hiring managers will probably want to learn more about what projects you’ve worked on and your main areas of expertise.

If you’re trying to find more prospects, look at open artificial intelligence jobs on a platform like Upwork.

AI developer FAQ

Now that you know a little more about what it takes to become an AI engineer, let’s cover a few outstanding questions you may have about the field.

What are my career paths as an AI developer?

AI developers have many different career paths. Some can get started by working as software engineers or data scientists. Others enter the field as machine learning engineers or research scientists. There are several ways someone can build a career as an AI developer, and one way isn’t necessarily better than the other options.

How can I gain practical experience as an AI developer?

You can gain hands-on experience by engaging in personal AI projects, participating in Kaggle competitions, contributing to open-source projects, and seeking internships or apprenticeships to gain hands-on experience. Talking with an experienced AI developer about how they prepared for their career may also be helpful.  

How long does it take to become an AI developer?

The time it takes to get started as an AI developer depends on several factors, such as your prior knowledge, educational background, learning pace, and the intensity of your learning efforts. Generally, it can take around four years of learning and applying AI methods (about the same time it takes to earn a bachelor’s degree) to gain the necessary skills and knowledge.

Start your AI developer career on Upwork

You have many paths to becoming an AI developer. In general, learning the fundamentals of machine learning and data analytics is a good idea. From there, you should start working on basic projects and building your portfolio to stand out on job applications. In time, you’ll be interviewing for your dream AI developer position.

If you’re looking for jobs in AI, check out Upwork’s marketplace of open projects and positions. Upwork maintains a massive database of full-time and freelance positions for talented individuals in various fields. Check out our list of open positions today to start looking for the role that’s right for you.

Disclosure: Upwork is an OpenAI partner, giving OpenAI customers and other businesses direct access to trusted expert independent professionals experienced in working with OpenAI technologies.

Upwork does not control, operate, or sponsor the other tools or services discussed in this article, which are only provided as potential options. Each reader and company should take the time to adequately analyze and determine the tools or services that would best fit their specific needs and situation.


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How To Become an AI Developer in 10 Steps
The Upwork Team

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