Thinking About A Career As A Quantum Machine Learning Engineer?
A new profession is about to rise
Quantum computing has the potential to be the most disruptive technology of the 21st century. It is a different form of computation that builds upon quantum mechanics, and it promises to solve problems we can’t solve with classical computers, such as the factorization of large numbers.
Quantum computing is moving from tech labs to mainstream commercial use
Quantum computing has evolved over the years. So have the career opportunities that this exciting technology offers. Quantum computing has long been a field for theoretical physicists and mathematicians only. But with the advent of real quantum computers and the availability of quantum simulators, quantum computing is moving from tech labs to mainstream commercial use.
This dramatic shift will affect which roles companies will hire in the future. Companies will hire quantum computing specialists beyond their research labs. They will demand experts who know how to tap the computational advantage of quantum algorithms into real business advantage.
One technology that will aid in turning the quantum advantage into business advantage is machine learning. Machine learning is already thriving in various sectors, from industry to finance, from self-driving cars to natural language processing. Yet, state-of-the-art machine learning models become extremely complex and, therefore, hard to train. While the inability to deliver such models could cause the next AI winter, quantum computing could be decisive to prevent us from such a scenario.
Our goal is to prevent from the next AI winter
But employing quantum computing to solve machine learning tasks demands a new profession that I would name “Quantum Machine Learning Engineer” or “Quantum Machine Learning Scientist.” Of course, there is a significant difference between an engineer and a scientist. With regard to quantum machine learning, however, the boundaries blur. To be successful, you’ll need to be both.