How to Get a Job in AI? Best Advice in a Fast-Moving Industry

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AI is one of the fastest-growing fields in the world today. To get a job in the AI industry, individuals need technical knowledge and skills that can be acquired in universities or by self-learning. The knowledge of computer programming languages such as Python, C++ and Java are crucial to get an AI job, however multi-billion dollar companies like Tesla, JP Morgan & Chase, Johnson & Johnson and Walmart are asking more than just programming knowledge from their AI job applicants.

Artificial intelligence (AI) is one of the fastest-growing fields in the world today, offering exciting career opportunities for those who want to shape the future of technology. This article explores the steps to get a job in AI, the skills you need to develop, and how to optimize your search for AI positions.

Learn how to get a job in AI and what multi-billion dollar companies like Tesla, JP Morgan & Chase, Johnson & Johnson, and Walmart are asking of their AI job applicants.

How to Get a Job in AI?

To get a job in the AI industry, individuals need technical knowledge and skills that can be acquired in universities or by self-learning with the help of online courses and books.

The knowledge of computer programming languages such as Python, C++, and Java is crucial to getting an AI job.

Getting a college degree in computer science and other related fields will give AI job applicants an edge over the competition, as recruiters often filter applicants by requiring a Bachelor’s or Master’s degree in computer science.

In addition to programming knowledge, the key technical skills that companies seek when hiring AI talent are:

  1. Machine learning 
  2. Deep learning 
  3. Artificial neural networks
  4. Natural language processing
  5. Computer vision 
  6. Big data
  7. Data analysis
  8. Business intelligence

Skills Needed to Land an AI Job

Whether you’re a recent graduate, a career switcher, or an experienced professional looking to pivot, it is crucial to understand the AI landscape.

Let us go through the above-mentioned skills briefly to get a better understanding of why they are required in AI jobs.

Machine Learning

Machine learning (ML) is a data science field that trains algorithms to imitate how humans learn to make autonomous, accurate decisions. ML is used to build AI systems. Therefore, it is considered a core technical skill in the AI industry.

Deep Learning

Deep learning and ML are often used interchangeably, but they are slightly different from each other. Deep learning can use larger and multiple data sources and can be used without human intervention.

Artificial Neural Networks

Artificial neural networks (ANNs) are networks of nodes that try to emulate the human brain. ANNs use data to learn and improve decision-making and accuracy. These networks can be fine-tuned to perform tasks such as image and speech recognition. The most well-known ANNs is Google’s search algorithm.

Natural Language Processing

Natural language processing (NLP) is an AI technology that allows computers to interpret text and speech. NLP is used in digital assistants (Siri, Alexa), voice-operated GPS systems, speech-to-text dictations, and more.

Computer Vision

Computer vision is an AI field that enables computers to identify and understand images and video. Computer vision technology is used in surveillance cameras, identification systems, text extraction tools, augmented reality (AR), autonomous vehicles, manufacturing industries, and more.

Data analysis

Data analysis is the process of analyzing data sets to gain valuable insights and draw informative conclusions about the data. The information gained from data analysis is used to aid decision-making and problem-solving

Big Data

Big data refers to advanced analytic techniques used to study and decipher large and diverse data sets from different sources and in different sizes. It is also used to identify business patterns and insights that can help reduce costs and make operations efficient.

Business intelligence

Business intelligence is a data analysis tool that produces reports, charts, and graphs from business data. 

AI Jobs in Various Industries

Now that we have learned about the technical skills for a head-start in how to start a career in AI let’s look at how AI is shaping the job markets in major industries from automotive to healthcare. This will help you understand which industry suits your skills and interests the best.


AI has revolutionized the automotive industry and has disrupted a wide range of activities, from product design to consumer financing.

For example, design software Autodesk is testing ways to design cars using AI. Big data is being used extensively to analyze and optimize supply chain networks and production lines. Banks are using AI and ML to analyze the creditworthiness of customers.

Ride-sharing startups are using AI to study daily routes taken by customers to offer the fastest carpool routes. Autonomous vehicles depend on AI and ML technology for key activities such as object identification, prediction modeling, speed regulation, and speech recognition. 


AI jobs can be found in the healthcare industry as biotech companies and drug makers look to incorporate the technology into a wide range of applications, including drug discovery, robot-assisted surgeries, preliminary diagnosis, remote consulting, and more.

As more devices are used to track health data and monitor patient conditions, big data, and AI are assisting in early detection and diagnosis of life-threatening diseases such as cardiac arrests and cancer.

Banking and Finance

Individuals seeking jobs in AI and data analysis technical skills may have an edge in landing jobs in the banking and finance industry, which is becoming increasingly reliant on big data and automation. Financial services companies deal with large volumes of customer and market data.

These corporations leverage AI to unearth valuable consumer insights, analyze markets, mitigate risks, detect fraud, and provide customer services.


The retail industry is also warming up to the technology and offering careers in artificial intelligence by using it for security and surveillance, supply chain and inventory management, marketing, customer engagement, and data analytics.

As you can see, jobs in AI have entered nearly every field of operations, and the demand for AI talent is expected to increase over time as more companies adopt the technology.

Real-World Examples of AI Jobs

Let’s look at some AI job listings from the above-mentioned industries to get an idea of how to get a job in AI.

Automotive: Tesla – Robotics Engineer

Here is what Tesla is looking for in its AI job listing for a robotics AI engineer at its Autopilot AI department.


  • Minimum three years of experience writing production-level Python or C++
  • Strong mathematical fundamentals 
  • Exposure to deep learning frameworks
  • Track record of training and deploying real-world neural

Finance: JP Morgan – ML Engineer

JP Morgan’s AI job listing for a machine learning and AI engineer required candidates to have the following qualifications:

  • Master’s degree with 1 or 2 years of experience or Ph.D. in computer science or machine learning
  • Knowledge in ML, graph learning, recommendation systems, network analysis, NLP
  • Technical ability in Python, Java, or Scala

Healthcare: Johnson & Johnson – AI Products Manager

The Manager, AI products job listing at J&J was a role responsible for developing and innovating AI and ML-enabled digital products for commercial, medical, and patient engagements. The requirements to begin this career in artificial intelligence were as follows:

  • Minimum Bachelor’s in computer science or information systems/technology
  • Minimum five years of business experience in analytics, management consulting, or project management fields
  • Experience with AI/ML-enabled product development 
  • Experience in applying AI/ML, quantitative methods, predictive mode line, and other analytics frameworks

Retail: Walmart – Senior Software Engineer, AI/ML

Walmart was hiring AI/ML software engineers to build AI-powered 3D model generation architectures for customer web experiences. The requirements for the job were:

  • Experience with 3D real-time rendering
  • Knowledge of programming languages: Java, Python, Bash, Spark (SQL, Streaming), Hadoop Map-reduce experience, Build Manager (Maven), Distributed Version Control (GIT), Continuous Integration (Jenkins)
  • Experience with GCS, BigQuery, Nvidia Toolkits
  • Experience with training got deep learning models

How and Where to Apply for AI Jobs?

Now that we have understood the landscape for jobs in AI let’s learn a few tips on where and how to apply for AI jobs.

  • You can start your job search on recruitment social platforms such as LinkedIn. 
  • You can also browse the ‘careers’ page of potential recruiter companies.
  • Make sure your résumé is up to date with your education and work experience information. 
  • Write a well-worded cover letter to introduce yourself.
  • Internships are great pathways to bagging a full-time job and gaining work experience.
  • Keep upskilling with the use of online courses and self-learning activities.
  • Build a strong professional network; Reach out to friends, peers, and colleagues in your field.
  • Participate in social activities such as hackathons and seminars.
  • Building a respectable online presence in your field of interest will boost your chance of landing the job.

The Bottom Line

With the right education, skills, and determination, getting a job in AI is an achievable goal. If you have a formal education in computer science and other related fields, you certainly have an edge over other applicants.

However, it must be noted that recruiters value experience over college degrees in the real world. Therefore, it is important to participate in internships and other activities to gain work experience.

Remember that AI is a dynamic and rapidly evolving field, so staying informed and continuously improving your skills is essential for a successful AI career.


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Mensholong Lepcha
Crypto & Blockchain Writer
Mensholong Lepcha
Crypto & Blockchain Writer

Mensholong is an experienced crypto and blockchain journalist, now a full-time writer at Techopedia. He has previously contributed news coverage and in-depth market analysis to, StockTwits, XBO, and other publications. He started his writing career at Reuters in 2017, covering global equity markets. In his free time, Mensholong loves watching football, finding new music, and buying BTC and ETH for his crypto portfolio.