The AI craze shows no signs of slowing down in 2024
Just when you thought the buzz couldn't get any better, the opposite is true: A new Slack survey of more than 10,000 white-collar workers around the world suggests the so-called “AI boom” is set to continue.
Survey results reveal a dramatic seven-fold increase in the urgency with which executives begin implementing AI in their operations, while a recent McKinsey “State of AI 2024” report revealed that AI adoption is set to soar from 50% to a staggering 72% globally.
The report further states that if 2023 was the year of AI discovery, 2024 will go down in history as the year of AI implementation, with employers already seeing benefits to revenue, employee productivity, and employee satisfaction.
These factors make 2024 a great time for aspiring professionals who can capitalize on the significant interest and newfound hype that artificial intelligence is generating, especially in the professional services sector.
So if you don't already have expertise in computer science, now's the time to consider a career in this ever-expanding field, especially since the artificial intelligence market, currently worth $200 billion, is predicted to soar to nearly $2 trillion by 2030.
And if you teeth As a 2024 graduate, you can use your expertise in computer science, mathematics, and other related fields to land five entry-level AI jobs that are in high demand as the AI implementation phase progresses.
(Salaries from Salary.com and Glassdoor.)
1. AI/ML Engineer
AI and Machine Learning Engineers design and deploy artificial intelligence and machine learning models and systems, and train models on extensive datasets.
Required Education and Qualifications
- Bachelor's degree in Computer Science or related field
- Specialized/advanced certifications in AI and machine learning offered through Coursera and other channels
Average salary range: $119,000 to $182,000
2. Data Scientist
Data scientists often use AI tools to collect, extract and make sense of data, which companies then use to improve decision-making.
Required Education and Qualifications
- Bachelor's degree in Computer Science or Data Science.
- Earning a data science certification online, such as the IBM Data Science Professional Certificate, allows you to enter the data science field without a degree.
Average salary range: $108,942 to $133,690
3. ML Researcher
ML (machine learning) researchers perform fundamental research that helps advance machine learning algorithms and enables new information science inventions.
Required Education and Qualifications
- Bachelor's degree and PhD in Computer Science, Mathematics, Machine Learning or Artificial Intelligence (preferred by most large tech companies).
Average salary range: $114,301 to $136,323
4. NLP Specialist
NLP (natural language processing) specialists work on applications that manipulate and interpret human language, such as chatbots.
Required Education and Qualifications
- Bachelor's degree in Computer Science or related field.
- Specialized courses covering topics such as Python, TensorFlow, PyTorch, and more.
Average salary range: $105,021 to $132,848
5. AI Software Developer
As an AI Software Developer, your role will focus on collaborating with data scientists to build AI software solutions and also integrating the solutions into existing applications.
- Bachelor's degree in Computer Science or related field.
- If necessary, take additional courses to understand Machine Learning concepts, NumPy, Pandas, Scikit-learn, Data Processing, etc. A Master's degree will be very helpful.
Average salary range: $106,000 to $157,000
Aspiring tech professionals should seize opportunities where their talents are in demand. … [+]
To secure these high-paying entry-level remote AI jobs, in addition to gaining hands-on experience in AI-related projects during your studies, don't forget to boost your experience and skills by earning a master's degree in a related specialization. This will go a long way in securing remote entry-level roles and attracting interest from large employers, including startups.
