Artificial Intelligence (AI) and machine learning is a rapidly expanding field thanks to the rapid development in technology which made real-life applications possible. The development of these technologies has led to several real-life applications in travel, healthcare, education, manufacturing, search engines, social media, and more which led to the increase in demand for AI and Machine Learning Engineers.
The State of AI and Machine Learning
There generally two types of artificial intelligence, Strong AI and Weak AI, and whenever we think of artificial intelligence the first thing that pops-up is super-intelligent computers that are sentient and have a digital form of consciousness that is similar to that of our own. These types of AI are referred to as Artificial General Intelligence or also known as Strong AI. AGI or Strong Ai still remains theoretical as no such system exists yet.
Weak AI is a type of AI that is designed for a specific type of task or solve a specific type of problem. Great examples of Weak AI are digital assistants in our smartphones and computers like Siri, Al, and Cortana. Weak AI only simulates human cognition by providing specific responses to commands based on programming.
Machine learning according to IBM “focuses on applications that learn from experience and improve their decision-making or predictive accuracy over time.” One great example of machine learning is when digital assistants like Siri or Alexa learn and respond to our voice commands.
AI and Machine Learning and the Role of Engineers
The position of the AI and Machine Learning Engineer is uniquely in the middle of software engineering and data science. These engineers use big data and programming frameworks to interface both software and hardware. They play an important role in creating programs that will enable machines to perform tasks that will help solve problems or provide solutions.
What is an AI and Machine Learning Engineer
The purpose of the AI and Machine Learning Engineer is to bridge the gap between theoretical models and real-world production models that are used in real-life applications. Engineers with data scientists to help translate data to machine learning programming. This means that they take the theoretical data science models and scale them to production-based models.
AI and Machine Learning Engineers create and develop algorithms that help AI and machines recognize patterns and understand commands.
What Are the Skills to Look for in an AI and Machine Learning Engineer
AI and Machine learning required in-depth knowledge in both data science and software engineering. Engineers should also have a grasp of data modeling and evaluation and should be able to apply theoretical models to real-life use cases. Engineers should have a strong background in mathematics and statistics.
General Skills Required
- Probability and Statistics
- Applied Mathematics
- Computer Languages
- Software Engineering
- Data Science
- Computer Science Fundamentals
- Data Modeling and Evaluation
- Application of Machine Learning Algorithms
Optional Specialization Skills
The Python programming language is the preferred programming language for machine learning. Python is an all-purpose programming language that deals with statistics and boasts a rich programming library and APIs.
TensorFlow is a Python framework open-source library that is for an end-to-end open-source machine learning platform. TensorFlow has a comprehensive, flexible ecosystem of tools, libraries, and other resources that help engineers build applications for machine learning.
Keras is a python based open-source library that helps engineers develop complex deep learning models. It is a broad platform that has ready-to-use interfaces that also support multiple back-end engines.
Pytorch is another widely used open-source deep learning framework and machine learning library.
AWS or Amazon Web Services provides a broad set of machine learning services and supporting cloud infrastructure. AWS provides machine learning services that allow engineers to build, train, and deploy machine learning models. AWS also provides AI services and ML infrastructure.
Important Information About the Field in AI and Machine Learning
The rise of real-world applications of Artificial Intelligence (AI) and Machine Learning (ML) has led to an increase in demand for the field of AI and Machine Learning Engineering. The field has been forecasted for high-growth in the coming years’ thanks to the growth of the demand of the machine learning market has grown from $1.4 billion to $8.8 billion in 2020 according to Research and Markets.
According to a recent study published by Indeed, a Machine Learning Engineer ranked number 1 on Indeed’s best jobs in 2019 with a 344% growth from, 2015 to 2018 with an average base salary of $146.085.
5 Highlights About the AI and Machine Learning Field
- High-growth in the field with a 344% growth from 2015 to 2018
- High average base salary of $146,000 according to Forbes
- One of the top fastest-growing jobs in the tech industry
- More and more businesses are adopting AI and Machine Learning
- The increased scale of demand as the Internet of Things (IoT) and Machine Learning Converge
Steps for Recruiting an AI and Machine Learning Engineer
The increased interest and rapid adaption of artificial intelligence and machine learning have led to an increase in demand for AI and Machine learning talent. With top businesses offering a salary package of at least $125,000 to $175,000 to qualified candidates.
Attract the right pool of talent by posting on specialized job boards that focus on IT and computer programmings related positions like Stack Overflow, GitHub Jobs, Dice, and more. Another great source of high-quality candidates is to partner with Universities through internships and job placements.
Hiring a recruiter that specialized in IT or computer engineering relevant positions helps you increase your reach through already established networks. For small businesses and start-ups joining AI conferences to help gain exposure and attract new talent.
Another way to attract top AI and Machine Learning candidates are to offer something beyond the ordinary salary compensation package. Providing prospective candidates with a glimpse of the company culture will help attract candidates who are looking for more than just a big paycheck.