With the fast evolution of Artificial Intelligence Applications, there is also a high demand for skilled and experienced AI Professionals. Remember that with the high access to huge amounts of data, Artificial Intelligence has become smarter, faster, more accurate and therefore more efficient. This only means that there is need for skilled software engineers to work alongside the increasingly growing AI applications.
Examples of Artificial Intelligence.
Many people think they have not come across Artificial Intelligence yet and it is far off from their reach. Think again. There are so many applications of Artificial Intelligence even in our day to day lives. You may have used Artificial Intelligence Applications more than you could even ever imagine.
Facial recognition and detection.
Have you used facial recognition on your phone to unlock it? Well there you have it. You have used Artificial Intelligence. There is also using virtual filters on our faces when taking pictures (yes! Snap chat and the likes). These are two examples of artificial intelligence that are now part of our daily lives. The former incorporates face detection, meaning any human face is identified. The latter uses face recognition through which a specific face is recognized.
Social Media regulation.
Social media applications are also using the support of AI to monitor content, suggest connections, and serve advertisements to targeted users, among many other tasks. These particular AI algorithms can spot and swiftly take down problematic posts that violate terms and conditions of a social media platform through keyword identification and visual image recognition.
Text editing (Auto correct).
Am quite sure you have used tools such as Grammarly as a student to check your final paper before submitting it to your teacher or may use it even now to check spelling in an email you hope to send to your boss. This is another example of artificial intelligence, you know. AI algorithms use machine learning, deep learning, and natural language processing to identify incorrect usage of language and suggest corrections in word processors and also texting applications.
Chatbots.
As a customer, interacting with customer service can be time-consuming and stressful, not to mention that replies could bot be as timely as you would want them to be. All that was made easier with Chatbots. This is where the use of AI chatbots becomes prevalent. The programmed algorithms enable machines to answer frequently asked questions, take and track orders, and direct calls.
Chatbots are taught to impersonate the conversational styles of customer representatives through natural language processing (NLP).
Digital Assistants.
Am sure you have ever resorted to ordering digital assistants to perform tasks on your behalf. When you are driving, you might ask the assistant to make calls for you or even tell you the weather forecast. A virtual assistant like Siri (for IPhone users) and Bixby (for Samsung users) is an example of an AI that will access your contacts as well as relevant Information in order to adhere to the commands that you give it. These assistants use NLP, ML, statistical analysis, and algorithmic execution to decide what you are asking for and try to do it according to your will. Voice and image search also work in much the same way.
Technical AI Skills currently in demand for an AI Software Engineer.
Machine Learning.
Machine learning provides machines with data from the past and with this data, machines are able to predict the future possibilities basing on the data from the past. It involves making predictions of future trends. The demand for Machine learning specialists is expected to grow by 40% in the next five years (as stated by the World Economic Forum) hence it is a skill that is highly needed by software engineers.
Programming skills.
For one to be considered highly skilled when it comes to software engineering, they need to be conversant with Programming languages for instance Java R, Python, Java Script and the likes.
Cloud computing.
Since most of the major industries are shifting from in house servers to cloud solutions, it will be advisable for software engineers to keep in the loop and take up skills like these.
Software Development.
This is the process of designing, creating and testing as well as maintaining different software applications. This is exactly what makes a software engineer. What then would be a software engineer without the capability to design and create software applications?
AI Ethics.
There is no way a software engineer will be able to market themselves without knowledge on Artificial Intelligence ethics. AI ethics are set of guidelines that stakeholders make use to ensure AI technology is developed and used responsibly.
Cyber Security.
Cyber security is one of the most sought after Software engineering skill as of 2024. Cyber security deals with identifying cyber attacks and suggesting recommendations to stop them or mitigating their impact.
Jobs that an AI software Engineer can do.
Big Data Analyst.
A big data analyst is meant to find meaningful patterns in data by looking at the past entries and using them to make predictions for the future.
Natural Language Processing Engineer.
In this role, one is meant to deeply explore the relationship between human language and computer systems. This involves looking at projects like chatbots and virtual assistants.
Researcher.
This role requires a software engineer to work with computer science and Artificial Intelligence Research. The engineer also needs to focus on discovering ways to enhance AI Technology.
Research Scientist.
A research scientist needs to be an expert in applied Mathew, machine Learning, deep learning as well as computational statistics.
Software Engineer.
A software engineer is meant to develop programs in which AI tools are meant to function.
Data Mining and Analysis.
This deals with handling large data sets and using them to study and identify anomalies and patterns to predict most possible outcomes in different situations or strategies.
Artificial Intelligence Engineer.
An AI engineer should be able to build Artificial Intelligence structures from scratch and also help stake holders to understand results that are attained from using these intelligent structures.
User Experience (UX) Developer.
The user experience developer works closely with customers to help them understand product functions and how to use the products easily. They also make research on how customers use products therefore deducting ways how computer scientists can improve in product designing through customer feedback.
Machine Learning Engineer.
These engineers make use of data to design, build and manage machine Learning (ML) software applications.
Robotics Engineer.
These are meant to design, build and test robots as well as robotic systems.
Computer vision Engineer.
These engineers develop and work on projects and systems that are involved with visual data.
Algorithm Developers.
These engineers are best at creating algorithms for Artificial Intelligence based applications.
Artificial Intelligence Ethicist.
These engineers are meant to focus on Artificial Intelligence ethics. They ensure that the entirely implications of AI technologies are co sidereal in their development and deployment.
Data Engineer.
A data engineer is meant to cater for Data analysis. This engineer should ensure that data is accessible for analysis and maintain proper data pipelines.
Data Scientist.
A data scientist is meant to collect, analyze and interpret data sets that are meant to be used in Artificial Intelligence applications.
Can Artificial Intelligence replace Software Engineers? In as much as Artificial Intelligence is becoming highly rampant in technological advancement, it still can not replace software engineers. They are much needed. The only change that needs to be incorporated in their work is learning how AI Systems work in order to be able to use them efficiently.
