AI Skills You’ll Want to Add to Your Resume, ASAP

March 14, 2024

Generative AI is having a big impact on the way companies conduct business today—making the technology front of mind for hiring managers across a range of industries.

Between Q4 2022 and Q2 2023 the number of generative AI jobs posted on Upwork increased by 1000%, and AI’s prevalence in the workforce continues to grow.

Companies that need help integrating generative AI into their workflows are often looking for talent with specific skills. By including the right terms in your resumes, cover letters, and proposals, you can find—and get hired for—new AI career opportunities.

AI’s role in today’s job market

You can find people working with AI in a wide range of roles, including:

Office manager
Administrative assistant
Scientist
Financial analyst
Conservation specialist
Law enforcement officer
Healthcare professional
Educator
Social worker
Operations manager
Building maintenance professional

Many roles and industries rely on AI to help streamline computer-based work. AI may analyze data, draft communications, create mockups, and more.

But you’ll also find the need for people with AI skills in industries that typically rely on manual labor, too. A forest ranger may use AI to assess data collected by sensors on animal trackers or park cameras, while a factory operations manager may use AI to help ensure that production lines are operating at peak efficiency.

These are jobs that AI won’t replace, but will rather improve the efficiencies and outcomes through collaboration.

Top artificial intelligence skills for resumes

You should mention any relevant AI techniques you have when discussing your experience. But the most in-demand AI skills to have on your resume or LinkedIn page right now include:

Prompt engineering
Programming languages for AI
Machine learning
Neural networks and deep learning
Natural language processing (NLP)
Cognitive computing skills

Spelling out these skills on your resume can help your job application catch the attention both human recruiters and any AI-powered applicant tracking systems they may be using, too!

Prompt engineering

Prompt engineering is the process of instructing large language models (LLMs) via text commands.

Sometimes prompts are very simple. For example, when I wanted ChatGPT to analyze a spreadsheet , I simply uploaded the file and stated the information I wanted.

Other prompts need to be more complex—such as this one, which I used when I asked ChatGPT to help develop an outline for a video:

The way you write a prompt can change the results generated by AI. And, because many AI tools—including ChatGPT—retain conversation history, you can craft prompts that layer on top of each other.

Skilled prompt engineers can coax high-quality, complex results out of AI tools by using the right requests.

Programming languages for AI

Programming skills are imperative to AI. Skilled programmers build and train the LLMs that power tools like ChatGPT—and they typically know one or more computer languages.

The most in-demand programming languages for AI programmers are:

Python: A general-purpose language often used in the development of generative AI applications
Java: A popular language used in machine learning algorithms and neural networks
R: A language used for data visualization and developing neural networks
Lisp: A 64-year-old programming language used to manipulate strings of data

If you know one of these languages and are interested in working with AI, you’ll want to be very specific about your skills and experience level. That said, AI tools like ChatGPT can help you continue to level up and even debug your code—just be careful not to share proprietary information with public tools!

Machine learning

Machine learning is a subset of artificial intelligence that automates data analysis and iterative learning. In part, it uses data to create accurate predictions.

You can find machine learning engineers working on e-commerce shopping recommendation algorithms, facial recognition programs, digital ad platforms, and more.

This prediction-based approach to AI is a central part of generative AI. As tools like ChatGPT become more and more commonplace, more companies will need skilled machine learning pros on hand.

Neural networks and deep learning

Neural networks are a complex approach to machine learning. In a neural network, multiple layers of processing connect to each other in nodes. These connections are structured so that information passxes through them in different ways, resulting in a variety of outputs.

If a neural network has more than three layers, it’s considered a deep learning algorithm. Being specific about any skills in or experience with neural networks and deep learning can help you find interesting companies to partner with and projects to work on.

Natural language processing (NLP)

NLP is a subset of computer science that’s focused on programming computers to understand language. Computer systems trained with NLP may be able to interpret written text as well as spoken audio—and produce responses that mimic our speech patterns, too.

When you use a conversational AI tool, you’re experiencing NLP in action. As more businesses roll out customer-facing AI applications, they’ll need NLP engineers to help make sure that the user experience is as natural and seamless as possible.

Cognitive computing skills

While NLP simulates human speech, cognitive computing attempts to mimic human thought. Cognitive computing engineers work to create computer systems that can recognize images, patterns, sentiment, risk, and more, and respond to these stimuli in a manner that is similar to how a person would respond.

However, we want to note that computers that don’t think or have cognitive abilities similar to a person’s. Instead, machines use statistical algorithms to learn patterns and predict outcomes. These outcomes can include human-like responses and behaviors.

That being said, the field of cognitive computing has many uses in a wide variety of industries, and leverages many other AI skills, including NLP, vision recognition, and human-computer interaction. This field is especially promising for highly regulated industries like banking, where a nuanced AI tool might be essential.

Demonstrating AI proficiency on your resume

Because hiring managers are often looking for very specific AI skills, you’ll want to be as clear as possible when writing a resume or proposal.

Simply saying you’re a programmer who knows “multiple languages” may not be enough to make your resume stand out. Indicating that you’re a pro with five years of experience using Python to build neural networks, though, can quickly land you on a company’s shortlist of great candidates.

Quantify your achievements

Assigning specific, quantifiable outcomes to your work in AI is also important.

A quantifiable outcome can be expressed as a countable number. For example:

Quantifiable skill statement: My team used AI-driven sentiment analysis to improve post-purchase customer satisfaction by 20%, quarter over quarter.
Non-quantifiable skill statement: I had my team use an AI text analysis tool to find customer pain points when shopping in our retail stores.
Quantifiable skill statement: By building a custom application that used machine learning to spot patterns in production line data, we reduced unexpected line shutdowns by 10%.
Non-quantifiable skill statement: We used ChatGPT to analyze data and improve efficiency at our London-area production facility.

You may not be able to quantify the outcome of every project you’ve ever worked on, and that’s okay. But try to do this whenever you can.

Highlight collaborative projects

AI is a very collaborative and cross-functional field. If a company wants to roll out a new chatbot to support its customer service team, you may find all of the following people working on the project:

Customer service representatives to provide input on needs
Copywriters to enhance the chatbot’s style and tone
User experience designers to build an appealing interface
AI engineers or developers to create the chatbot’s algorithms
Cybersecurity advisors to ensure that sensitive information is protected
Social media managers to promote the new chat experience to customers

If you’ve worked on AI projects with people from different teams, mention this! It shows that you’re ready to jump in and work collaboratively with others at a new company.

Stay updated and obtain certifications

The field of AI changes rapidly. To grow your career in the industry at a comparable pace, you’ll need to focus on ongoing AI education and upskilling.

While you can in theory grow your AI knowledge and career without taking any structured courses, getting an AI certification can help you learn new skills quickly and showcase your commitment to the field.

You can find free and low-cost course options on platforms like Coursera and Udemy, or pursue a more formal education path with graduate certificates from Stanford University, among others.

How to write an AI resume

You can adapt your existing resume template to highlight your AI achievements and skills by simply working the relevant terms and explanations into your job duties and professional summary.

If you’re applying for a job for the first time, then try this resume outline as a starting point:

Name and contact information
Any AI certifications, coursework, and educational experiences
Resume summary, with a highlight on your AI experience
Work experience section—including years of employment and quantifiable outcomes of your work in each job description
AI skills section to provide a bulleted overview of specific, relevant skills (like using AI models, predictive modeling frameworks, neural networks, ChatGPT prompt engineering, and more)

(If you’re feeling stuck, you can find professional resume writers and resume builders)

Soft skills for AI professionals

A successful career in AI isn’t all about technical skills, though. You’ll need to work on developing a variety of soft skills—particularly those related to thinking through problems, facing change head-on, and communicating with others.

Some soft skill sets you may want to highlight on your resume include:

Adaptability
Communication
Creativity
Critical thinking and problem-solving
Emotional intelligence

You don’t need to list these skills out in a row—instead, try working them into your descriptions of jobs and projects like this:

“In this role, I led a cross-functional team of five to evaluate problems in current workflows and develop generative AI solutions. When deployed, our solutions led to a 10% increase in delivery speed.

Leveraging AI skills in interviews

If your resume catches the attention of a hiring manager, you may be asked to interview—so you’ll want to be prepared to talk about your skills verbally!

Practice discussing your work in the following ways:

Explain your experiences in quantifiable terms, just like on your resume
Walk the interviewer through how your AI skills have evolved over time and show that you’re committed to growth
Reference specific machine-learning skills and concepts when discussing your approach to real or hypothetical problems
Explain how you used specific soft and hard skills to address a problem on one of your recent projects
Be familiar with the history and background of your AI skills—such as how Python use has evolved over time
Mention any other AI skills that, even if they’re not your specialty, you’ve been exposed to through your work

You can try practicing these statements by yourself, or with a friend. You can even ask ChatGPT to act as an interviewer and create questions for you to answer in real-time.

Talk about other related experiences

While some people have spent their entire career in AI, you aren’t alone if you’ve only moved into this field recently. Don’t hesitate to still talk about your previous professional experiences and how they help you in your current AI work.

Software engineers can discuss how their approach to software development has changed with the help of AI
Data scientists might reference how the skills they obtained in their data science work without AI influence the way they interact with the technology now
Writers could explain how much time AI is saving them when it comes to editing and optimizing content for website
Graphic designers may want to discuss how they use AI to create more mockups, versions, and ideas faster than ever before

AI skills equal freelancing opportunities

No matter where you currently are in your AI career, continuing to evolve, define, and explain your skills can help you land more opportunities—including independent work.

49% of hiring managers expect to hire more independent talent as a result of increased generative AI use. They need people on their teams who can use generative AI and think of new ways to leverage these tools’ capabilities.

You can then fill out each section of your profile with more information—this is a perfect spot to share quantifiable details about your success and any related AI skills.

This article originally appeared on Upwork and was syndicated by MediaFeed.org.