How To Become an AI Engineer (Plus Job Duties and Skills)

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Updated August 7, 2024

[POP MUSIC] Machine learning engineer. A machine learning engineer is a skilled programmer who designs algorithms that allow machines to function without direct human assistance with the goal of total automation. They need to be skilled in Python, Java, C, C plus plus, R, statistics, data structures, algorithms, and data modeling. How do you become one? You'll need a degree in computer science or related field, and strong data science and software development knowledge. To stand out during your job search, consider an AWS machine learning certification issued by Harvard, MIT, or Stanford. Here are four tips to help you land a job in the tech industry. Do your research. The tech industry is constantly changing, and access to high-value skills is available through non-traditional routes like bootcamps. Research the roles you're interested in, and develop a plan to help you get there. Update your resume. Tailoring your resume is one of the most important parts of the job search process. And highlighting your concrete technical skills is a must in tech. For tips on how to create a standout resume, click here. Use your network. Reach out to fellow techies you know who can tell you what life in the industry is really like. Connecting with people from your bootcamp, college courses, or workplaces can open doors to new opportunities you may not have considered yet. Be open. Getting a tech job doesn't just mean working at a tech company. Tech jobs are available anywhere technology is used. Keep an eye out for areas that need someone just like you. If you learned something new or got inspired to pursue a career in tech, hit the Like button and subscribe to our channel. And if you're actively interviewing for a role in tech, check out this playlist for tips to help you succeed. Thank you so much for watching. See you next time.
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Artificial intelligence (AI) engineering is a fast-growing industry that can provide you with new challenges and opportunities for professional development. If you're interested in the latest technologies, you might want to pursue a career as an AI engineer. By learning more about the role and the steps required to start this career, you can better decide if this is a career for you.In this article, we explain what an AI engineer is, explore some of their responsibilities, detail the importance of this role and list the steps you can take to become an artificial intelligence engineer, along with their key skills.Key takeaways:
  • An AI engineer is a professional who develops, programs and trains complex networks of algorithms that make up artificial intelligence, similar to how a human brain functions.
  • AI engineers can have an impact on the overall success of an organization by developing advanced machine learning models that provide valuable insight into future potential concerns in fields such as health care and finance.
  • To become an AI engineer, you require certain education qualifications, such as a bachelor's degree in a relevant field like computer science and some employers might prefer a graduate degree; gaining practical experience through internships, part-time jobs and personal projects is also beneficial.

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What is an AI engineer?

An AI engineer is a professional who's responsible for developing, programming and training the complex networks of algorithms that make up AI so that they can function like a human brain. This role requires combined expertise in software development, programming, data science and data engineering.Though this career relates to data engineering, companies rarely require AI engineers to write the code that develops scalable data sharing. Instead, artificial intelligence developers locate and pull data from a variety of sources and create, develop and test machine learning models. They then use application program interface (API) calls or embedded code to build and implement AI applications.Related: What Is Artificial Intelligence?

What does an AI engineer do?

AI engineers are primarily responsible for using various programming algorithms to build, test and deploy AI models. Some of their other duties include:
  • Coordinating with other team members
  • Creating and managing the AI development process and overall infrastructure of a product
  • Conducting statistical analysis and interpreting the results to guide an organization's decision-making process
  • Automating important infrastructure for the data science team
  • Developing infrastructures for data transformation and ingestion
  • Building AI models that make predictions based on large quantities of data
  • Explaining the usefulness of the AI models they create to a wide range of individuals within the organization, including collaborators and product managers
  • Transforming the machine learning models into APIs to interact with other applications
Related: Learn About Being a Data Scientist

Why are AI engineers important?

Machine learning and artificial intelligence are developing specialties that can have a large impact on the overall success of an organization. This is because information technology professionals who decide to pursue a career in AI can develop advanced machine learning models that provide valuable recommendations and insight into future issues or decisions. Some fields that use this technology include:
  • Finance: In the finance industry, many organizations use AI to learn the habits of users to better identify suspicious or fraudulent activity.
  • Manufacturing: Manufacturing organizations use AI models to reorganize their supply chain for better efficiency, predict maintenance issues and integrate with technological systems. As a result, these companies can manufacture products more safely and inexpensively.
  • Health care: The health care industry has many processes that use a great deal of time and resources. By using AI, organizations can reduce the cost and time associated with things like drug discovery.
  • Enterprises: Many businesses use AI to identify important insights in otherwise unstructured data, such as social media.
Related: Learn About Being a Software Engineer

How to become an AI engineer

There are many paths you can take to become an AI developer. If you're hoping to begin a career as an AI engineer, consider following these steps:

1. Earn your bachelor's degree

To get a role as an artificial intelligence engineer, you likely have to meet certain education requirements. Employers often require candidates to have a bachelor's degree in a related field, such as:
  • Computer science
  • Data science
  • Information technology
  • Statistics
  • Finance
Earning a bachelor's degree provides you with a strong foundational knowledge of computer and technology concepts. It also gives you the opportunity to work on AI-related projects, allowing you to gain experience before entering the career.

2. Consider a graduate degree

Though not typically required, earning a master's degree in a related field may help you develop your skill set, improve your eligibility for AI engineering positions and boost your earning potential. Some fields of study to consider include:
  • Data science
  • Cognitive science
  • Mathematics
  • Computer science
Related: Should I Get a Master's Degree? 9 Factors To Consider

3. Take additional courses and pursue relevant certifications

There are online courses and certifications you can pursue to further develop your knowledge and skills in the field of AI. Some courses require a fee, while others are free. Start by browsing available courses to see which ones can best expand your skills. Then, you can browse through certifications and consider which may improve your resume based on the type of job you want.

4. Earn experience

There are several ways to earn related experience before working as an AI engineer. Gaining experience gives you practical knowledge of how to implement AI solutions in various ways and can help you build a stronger resume.One way to earn relevant experience is through an internship. Many college degree programs require an internship, but even if yours doesn't, completing an internship voluntarily can provide you with experience.Another way to gain experience is through a part-time job. Look for organizations that have AI engineers in need of part-time assistance. While you may not work directly on AI projects, you can still observe how AI engineers work and the type of projects they complete.Building your own AI projects helps you to discover what areas to improve on and how to optimize the development process. You can then use this project to highlight your abilities with AI during a job interview.Related: 19 Tips for a Fantastic Internship

5. Prepare for the job search

When you start looking for AI engineer positions, try to identify opportunities that match your level of education and experience. For example, if you don't have a master's degree, you can narrow your search to organizations that want AI developers with bachelor's degrees. This can save you time by only applying to jobs that fit your skill, education and experience levels.It's also important to have a professional resume before applying for an open position. On your resume, list your best attributes and accomplishments related to your AI work. Before submitting your resume, it's a good idea to ask others to review it for you. They may have suggestions for other things to include, advise you on how to better describe yourself or notice mistakes to correct.
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Key skills for AI engineers

AI engineers use a range of skills to help them succeed in their careers. By developing these skills, you may become a better AI engineer. Some of the key skills of AI engineers include:

Understanding of statistics, probability and linear algebra

AI engineers build models using algorithms, which rely on statistics, algebra and calculus. Having advanced skills in mathematics helps AI engineers build more complicated projects. Additionally, it's helpful to have familiarity with probability so that you can interact with some of artificial intelligence's common machine learning models, including Hidden Markov, Gaussian mixture and Naive Bayes models.Related: Math Skills: Definition, Examples and How To Develop Them

Programming skills

It's helpful for AI engineers to have a firm understanding of popular programming languages, like C++, Java, R and Python. These programming languages help AI engineers to develop and deploy artificial intelligence models. Knowing multiple programming languages also helps them work on a wider range of projects and makes it easier to convert a project from one language to another.Related: How To Become a Better Programmer (With Skills To Develop)

Analytical skills

Projects often require AI engineers to review and interpret important data. For example, they may need to assess the output of an AI application to ensure its results are reasonable. To do this effectively, it's helpful to be able to analyze information, develop insights and brainstorm possible solutions.Related: Analytical Skills in the Workplace: Definitions and Examples

Business knowledge

Successful artificial intelligence projects can solve an organization's major issues. Possessing business knowledge allows you to convert your technical ideas into effective business projects. Regardless of what industry you're working in, it's beneficial to have a basic understanding of how the business operates, its target audience and the organization's competitors within the market.

Communication skills

Artificial intelligence developers often need to communicate data and technical information to a wide range of individuals with varying degrees of technological knowledge. For example, employers might ask you to implement and present a new AI model to every department in an organization.For this reason, it's beneficial to be an excellent verbal and written communicator. This includes being able to take the complex topic of artificial intelligence and explain the core elements to someone without advanced technical knowledge.Related: Top 10 Communication Skills for Career Success

Collaboration skills

Individuals in this field often work within a team of other AI developers and IT professionals, so it's helpful to possess the ability to work efficiently and effectively within a team. For example, a group may work on an AI project simultaneously, with each AI engineer working on separate parts. AI engineers have the ability to work within this group setting, ensuring that their piece of the project aligns with the other components.Related: Collaboration Skills: Definition and Examples

Critical thinking skills

To create innovative AI models and solutions, it's helpful to have critical thinking skills.  This means finding a variety of possible solutions to a single problem. Critical thinking skills help you to analyze a problem in multiple ways and design multiple solutions.Please note that none of the companies mentioned in this article are affiliated with Indeed.
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