Demand for jobs in the AI field skyrockets as LinkedIn Report 2020 projected artificial intelligence specialists to be its number one emerging job with a 74 percent annual growth rate within the past four years.
The report puts AI job roles such as AI specialists and AI engineers in the limelight while it outpaced robotics engineer by 40 percent during the same duration, data scientists by 37 percent, full-stack engineer by 35 percent, and site reliability engineer by 34 percent.
For LinkedIn to conclude meticulously, they had to crunch data from all its available public profiles from the past five years.
Interesting, isn’t it?
Even so, the AI field comes with rather high expectations from candidates. Large organizations and employers are strictly looking for highly skilled AI professionals in deep learning, machine learning, natural processing language (NLP), TensorFlow, and programming languages such as Python. These skills would rather take some time for professionals to master. In short, individuals with a solid background in mathematics and programming will be highly preferred.
The AI talent is hot right now, thus, creating 133 million new AI jobs for AI professionals by 2022 predicts The World Economic Forum.
- According to Gartner, the business value AI market creates will reach USD 3.9 trillion by 2022.
- McKinsey Global Institute says AI and machine learning has the capability of creating an additional value of USD 2.6 trillion for marketing and sales by the end of 2020. And USD 2 trillion in the manufacturing and supply chain planning sector.
But what’s the real deal with AI engineers?
Further on, we will cover topics related to: –
- Their job profile
- Roles and responsibilities
- What other tasks does an AI engineer do?
What’s the job profile of AI engineers?
An AI engineer helps in building, testing and deploying machine learning models. They hold responsible for maintaining the AI infrastructure likewise. They pose themselves as problem-solvers by providing solutions both to software development and machine learning. For the individual to have a deeper understanding of the job role, they need to have strong knowledge in machine learning.
Machine learning is known to use large datasets to learn from them without needing to be programmed. That is, they can learn from the data that is fed inside the machine learning algorithms.
Roles and responsibilities
Based on the type of industry, an AI engineer could play multiple roles. Let us have a look at the most common responsibility.
- Automate infrastructure that is used by the data science team.
- Transform machine learning models into APIs providing easy access to other applications.
- Coordination between data scientists and business analysts within the organization.
- Testing and deployment of these models.
- Automate processes with the help of machine learning.
- Development of products using machine learning algorithms.
What other tasks does an AI engineer do?
As we can see, the day to day task of AI engineers is not easy. Depending on the type of industry, multiple responsibilities need to be taken up. Such responsibilities include: –
- Utilizing machine learning on datasets inputs in a software development cycle.
- Improvements while researching machine learning algorithms.
- Pattern matching and pattern recognizing.
- Data mining.
- Train the machine learning-based software for tasks such as object detection, image recognition, autonomous vehicle, and bioinformatics.
What are the skills required?
Below are the exact skills you need to acquire to get a job in the AI field.
- Programming skills – R, Python, Java, C++
- Machine learning algorithms – Naïve Bayes, KNN, Support Vector Machine
- Frameworks – PyTorch, Theano, Caffe, and TensorFlow
- Spark and big data technologies such as Hadoop, MongoDB, and Cassandra
An AI engineer is likely to earn an average salary package of USD 114,121 per annum in the US, a report taken from Glassdoor.
AI is here to transform the lives of many while making the work structure of humans easier. As companies look forward to adopting technologies like machine learning, AI, and deep learning, it is crucial to forming a baseline in understanding all these terms.
Fortunately, the online certification program now becomes critical as we move away from traditional practices. This means it is now important to up skill and learn more about what these technologies are capable of.
In the next few years, these technologies will become an important part of your workflow. Therefore,you need to learn as much as possible about technology and upgrade your skillset.
You can find multiple online resources that can help you out. The Artificial Intelligence Board of America (ARTIBA) also provides an interesting breakdown of AI including certification programs for aspiring AI professionals.
Why take up a certification program from ARTIBA?
- ARTIBA touts as a demanding and performance-based certification provider found online.
- It is considered one of the industry’s proven comprehensive online AI certification.
- ARTIBA certification covers a wide variety of AI skills the current industry is looking to hire.
- Indicates a high level of mastery in the AI field.
- It is popular, renowned, and well-regarded coursework on AI.
- Career-focused certification program for tech programmers who wish to transform their careers in the AI field.
Are you ready to rise and find victory in the AI world?