AI is a booming industry with job postings up 68% since 2022. If you’re looking for a role working with this evolving technology, you’re in the right place. Let’s explore how to break into this industry and what you need to know.
What Is AI, Exactly?
There’s been a lot of hype in recent years about artificial intelligence (AI), and with good reason. This exciting technology seems to have exploded onto the scene out of nowhere.
That’s not entirely true, though. The foundations for AI have been around since the 1940s with the first neural networks that led to the development of machine learning. Machine learning is, essentially, algorithms that adapt and improve as they process more data. AI tools, in turn, are programs that reason, act, and adapt based on the data being collected and processed by their algorithms.
In short: AI is an artificial neural network created by multiple sets of algorithms processing massive amounts of data.
If that sounds like something out of science fiction, you’re not wrong. However, AI is here to stay and only improving over time, and it’s an exciting field to get into with the right skills.
How to Get a Job in Artificial Intelligence
1. Pick an AI Career Path
Your first step is to identify what career path you want to explore. Many different careers work with or are impacted by AI, from healthcare and household products to government and data analysis. Here are a few roles you might consider as you explore:
- AI engineer: Develops the tools and software to deploy AI in the real world.
- Machine learning engineer: Builds and deploys AI models.
- Data scientist: Analyzes and interprets complex data.
- AI product manager: Helps companies integrate AI into their products.
- AI ethics specialist: Focuses on responsible, unbiased AI practices.
- Software developer: Create AI-powered products and programs.
Your first step is to decide whether you want to work toward building new, better AI systems or if you want to use the models and tools already available to augment your role.
2. Learn the Fundamentals
AI jobs require a solid understanding of several fundamentals. Fortunately, you don’t need a degree to learn them. Online courses, bootcamps, and self-study resources make AI more accessible than ever. Here’s some of what you’ll need to know:
- Programming: Python is the most widely used programming language in AI. Learn frameworks like TensorFlow, PyTorch, NumPy, and scikit-learn.
- Mathematics: Basic knowledge of linear algebra, probability, and statistics can help you get ahead.
- Machine learning (ML): Understand supervised and unsupervised learning, neural networks, and model training.
- Data handling: AI models rely on solid data, so it’s important to learn how to clean, analyze, and visualize datasets.
- Software development: Understanding how to build programs can set you up for success in the AI field.
Check out platforms like SkillUp, Coursera, Udacity, and freeCodeCamp to find courses and start building your toolkit.
3. Develop Real-World Experience
The best way to stand out to potential employers is by demonstrating real-world experience. Start by working on small AI projects like these:
- Chatbots: Build a chatbot using Python and NLP libraries.
- Image recognition programs: Train an AI model to identify objects in images.
- Predictive analytics: Use machine learning to forecast trends or behaviors.
- AI-powered apps: Integrate AI into an app, like a system to recommend books or restaurants.
Publish your projects on GitHub or create a portfolio website to showcase your work to potential employers. Make sure your online portfolio is included in your LinkedIn profile, job application information, and resume.
4. Gain Certifications & Take Online Courses
If you’re following our advice in Step 2, you’ll likely get a few of these under your belt. However, additional certifications can boost your resume. Consider courses and certifications like these:
5. Network
Once you’ve built your foundation and learned the necessary skills to work in AI, networking and connecting will be your top priority. Join meetups, webinars, online groups, forums, or workshops to become part of the AI community. From there, connect with professionals already in the field and seek mentorship. Develop an attitude of openness and curiosity as you make connections in your new industry.
6. Prepare Your Resume & Portfolio
Now it’s time to show what you’ve learned and get your resume in front of AI companies. Customize your resume to highlight the skills, projects, and achievements you have that are relevant to the role you’re applying for.
If you haven’t already made a portfolio website, now’s the time. Make sure it’s updated with your latest projects so you can quickly showcase your skills and experience.
And, yes, you should write a cover letter—and try not to use generative AI for this. Your cover letter should introduce the hiring manager to who you are and why you’re qualified for this role. The human element is still valuable in the job hunt process! Focus on showcasing your abilities, and let your portfolio show off your AI skills.
7. Prepare for Interviews
The last step of how to get an AI job is to prepare for the interview process. You can expect the classic interview questions along with more challenging, technical questions. You might face a coding challenge, problem-solving questions, or discussions about your AI projects. Make sure to refresh your skills and coding knowledge before you go into the interview.
And don’t forget: all the usual interview prep tips still apply!
Artificial Intelligence Jobs to Consider
As we mentioned earlier, there are many different jobs to choose from in the world of AI. Let’s get into the specifics of some up-and-coming roles you might choose.
Artificial Intelligence Engineer
These professionals use AI and ML techniques to develop apps and systems. They develop the tools and processes so AI can be used for real-world problems.
The average salary for an AI engineer ranges from $127,000 to $197,000.
Machine Learning Engineer
ML engineers are the ones who research, build, and design AI systems. They often work with data scientists and are the ones deep in the nitty-gritty of the data and models behind AI systems.
The average salary for a machine learning engineer ranges from $135,000 to $216,000.
Data Engineer
Data engineers are responsible for the systems that collect and process data into information that data scientists and analysts can use. This role has opportunities in practically every industry.
The average salary for a data engineer ranges from $111,000 to $164,000.
Robotics Engineer
In short, robotics engineers develop robots. They might design new products or test prototypes for a wide range of industries. This role combines mechanical and electrical engineering with computer science.
The average salary for a robotics engineer ranges from $119,000 to $210,000.
Software Developer
Software developers create programs for computers and various apps. In the AI field, they may work on programs that integrate AI. Typically, software engineers are analytical and enjoy working with digital systems.
The average salary for a software developer ranges from $130,000 to $209,000.
Data Scientist
A data scientist works with the information collected and processed by a data engineer. They use this data to answer whatever questions their team or organization is asking and often develop predictive models to forecast outcomes.
The average salary for a data scientist ranges from $131,000 to $212,000.
It’s Not Science Fiction—It’s Your Next Job
You don’t automatically need a computer science degree to land a job in AI; you need skills, hands-on experience, and persistence. Whether you’re just entering the workforce or you’re ready for a different challenge, SkillUp has tools to help you achieve your career goals:
Online training programs
Career coaching Career exploration pathways
Free career resources Pick a path, build AI projects, and start applying! We’re here to help you along the way.
