Artificial intelligence (AI) is one of the fastest-growing fields in the world today and offers exciting career opportunities for those who want to shape the future of technology.
Below we’ll explain the steps you need to take to find a job in the AI sector, what skills are required, and how you can optimize your job search.
How do you get a job in AI?
Anyone seeking a job in the AI industry needs technical knowledge and skills that can be acquired at universities or through self-study through online courses and specialist literature.
Knowledge of computer programming languages such as Python, C++, and Java plays a crucial role when applying for an AI job.
A college degree in computer science and other related fields gives candidates for AI jobs a competitive advantage, as hiring managers often list a bachelor’s or master’s degree in computer science as a requirement when selecting applicants.
In addition to programming skills, key technical skills companies look for when hiring AI talent include:
- Machine learning
- Deep learning
- Artificial neural networks
- Natural Language Processing
- Computer Vision
- Big Data
- Data analysis
- Business intelligence
Required expertise for an AI job
Regardless of whether you have just graduated, are reorienting your career, or are an experienced professional looking for a change – it is important to understand the AI landscape.
To better illustrate why the above skills are needed for AI jobs, let’s briefly go through them all.
Machine learning
Machine learning (ML) is a field of data science that uses algorithms to mimic human learning processes in making autonomous, accurate decisions.
AI systems are developed using ML. Therefore, it is considered a key technical skill in the AI industry.
Deep learning
Deep learning and ML are often used interchangeably, but they differ slightly from each other.
Deep learning can use larger or multiple data sources and can be used without human intervention.
Artificial neural networks
Artificial neural networks (ANN) are networks of nodes that attempt to imitate the human brain.
To learn and improve decision making and accuracy, ANNs work with data.
These networks can be fine-tuned to perform tasks such as image and speech recognition. The most famous ANN is Google‘s search algorithm.
Natural Language Processing
Natural language processing (NLP) is an AI technology that helps computers interpret text and speech.
NLP is used in digital assistants (Siri, Alexa), voice-controlled GPS systems, speech-to-text programs, and more.
Computer Vision
Computer vision is a field of artificial intelligence that allows computers to recognize and understand images and videos.
The image processing technology is used in surveillance cameras, identification systems, text extraction tools, augmented reality (AR), autonomous vehicles, and the manufacturing industry, among other things.
Data analysis
Data analysis is the process of analyzing data sets to extract valuable insights and informative key results from the data.
The information resulting from data analysis is used for decision-making and problem-solving.
Big Data
Big data refers to advanced data analysis techniques used to examine and decipher large and diverse data sets from various sources and of various sizes.
They are also used to capture business processes and insights that can help reduce costs and increase efficiency.
Business intelligence
Business intelligence is a data analysis tool used to create reports, charts, and graphs based on business data.
AI jobs in different industries
Now that the technical skills needed to launch an AI career are clarified, let’s look at the impact of technology on labor markets in major industries, from automotive to healthcare.
This makes it easier for you to find out which industry best suits your skills and interests.
Automobile manufacturing
AI has revolutionized the automotive industry and changed a variety of processes – from product design to customer financing.
For example, the design software Autodesk is testing possibilities for designing cars using AI.
Big data is used extensively to analyze and optimize supply chain networks and production lines. Banks use AI and ML to analyze customers’ creditworthiness.
Ridesharing startups use AI to study their customers’ daily routes to offer the fastest ridesharing connections.
Autonomous vehicles rely on AI and ML technologies for critical tasks such as object detection, predictive modeling, cruise control, and speech recognition.
Healthcare
AI jobs abound in healthcare as biotech companies and drugmakers look to use the technology for a variety of applications, such as B. for drug research, robot-assisted surgeries, preliminary diagnoses, remote consultation, and much more.
As more devices are used to collect health data and monitor patient conditions, big data and AI are helping in the early detection and diagnosis of life-threatening diseases such as cardiac arrest and cancer.
Banking and Finance
People who want a job in AI and data analytics and have technical skills may have an advantage in hiring in the banking and finance industry, which is increasingly reliant on big data and automation.
Financial service providers deal with large amounts of customer and market data.
These organizations use AI to gain valuable insights about their customers, analyze markets, mitigate risk, detect fraud, and provide customer service.
retail trade
Retail is also opening up to technology and offering career opportunities in the field of artificial intelligence.
It is used for security and surveillance, supply chain and inventory management, marketing, customer loyalty and data analysis.
The demand for AI talent is expected to continue to increase over time as more companies implement the technology.
Real-world examples of AI jobs
Let’s look at some AI job postings from the above industries to get an idea of how to find a job in the AI sector.
Vehicle construction: Tesla – robotics engineer
Here’s what Tesla is looking for in the job posting for an AI Robotics Engineer for its Autopilot AI division.
Requirements:
- Min. 3 years of experience programming with Python or C++ at a production level;
- Strong basic mathematical skills;
- Experience with deep learning frameworks;
- Track record of training and implementing neural networks in practice.
Finance: JP Morgan – ML Engineer
JP Morgan’s job posting for a Machine Learning and AI Engineer included the following requirements for applicants:
- Master’s degree with 1 or 2 years of experience or PhD in computer science or machine learning;
- Knowledge of ML, graph learning, recommendation systems, network analysis, NLP;
- Technical skills in Python, Java, or Scala.
Healthcare: Johnson & Johnson – AI Products Manager
The “ Manager, AI Products ” job opportunity at J&J covered the development and innovation of AI and ML-powered digital products for commercial, medical, and patient applications.
The requirements for entering the professional field of artificial intelligence were as follows:
- Minimum of a bachelor’s degree in computer science or information systems/technology;
- At least 5 years of professional experience in the areas of analytics, management consulting or project management;
- Experience with AI/ML-powered product development;
- Experience in applying AI/ML, quantitative methods, predictive mode line, and other analytical methods.
Retail: Walmart – Senior Software Engineer, AI/ML
Walmart was looking for AI/ML software engineers to develop AI-powered 3D model generation architectures for online customer experiences.
The requirements for this position were:
- Experience with real-time 3D rendering;
- Knowledge of programming languages Java, Python, Bash, Spark (SQL, Streaming), experience with Hadoop MapReduce, Build Manager (Maven), distributed version control (GIT), continuous integration (Jenkins);
- Experience with GCS, BigQuery, and Nvidia Toolkits;
- Experience training deep learning models.
How and where can you apply for AI positions?
Now that we understand the situation in the artificial intelligence job market, let’s get some tips on where and how to apply for AI positions.
- You can start your job search on social platforms like LinkedIn.
- You can also browse the job board of potential companies offering a position.
- Make sure your resume is up to date and includes your education and work experience.
- Write a well-worded cover letter introducing yourself.
- Internships are a great way to get a full-time job and gain work experience.
- Continuously educate yourself through online courses and self-study.
- Build a strong professional network: Reach out to friends, peers, and colleagues.
- Participate in events such as hackathons and seminars.
- Building a respectable online presence in your area of interest will also increase your chances of getting a job.
Conclusion
With the right training, skills, and determination, a job in artificial intelligence is an achievable goal.
If you have a degree in computer science and related fields of study, you will certainly have an advantage over other applicants.
However, it is important to remember that HR managers place more value on experience than on a university degree. It is therefore important to take part in internships and other activities to gain professional experience.
Remember that AI is a dynamic and rapidly evolving field. Staying current and continually improving your skills is crucial to a successful AI career.