Last updated: February 1, 2018
If you’re looking for an exciting career in an emerging tech field, look no further than a job in AI engineering. Even though this is one of the fastest-growing jobs in the technological sector, the demand far outpaces the number of qualified applicants. According to a 2014 Pew Research study on Future Jobs, artificial intelligence will permeate our daily lives by 2025, displacing many jobs in the process but also creating new career opportunities for those with the right skills.
What Exactly Does an AI Engineer Do?
AI engineering falls into the greater purview of the growing artificial intelligence field. Some AI engineers get their start in software engineering and then move into AI, while others come from unique backgrounds such as biology, according to IEEE. This is a constantly-changing field where agility is key, so the skill requirements will be as unique as the organization you work for, however as a general lay of the land here is some useful information adapted from a subject matter expert on Quora:
AI or machine learning researcher: Research and discover improvements to machine learning and robotic algorithms. In some cases, find out ways to apply these theories to new domains. In many cases, people in these positions will hold an advanced degree such as a Masters or Ph.D. in a STEM-field.
AI software development, program management, and research: Building the systems and infrastructure that can apply machine learning to a given data input set. Most of these jobs are held by people who have an undergraduate degree in a related field like computer science, engineering, etc. These positions are an excellent fit for individuals with some understanding of AI, robotics, and strong mathematical skills.
Data mining and analysis: A deep-dive investigation of large data sources, often involving the creation and training of systems to recognize patterns. Ph.Ds are not unheard of in these roles, but positions can be filled by highly experienced professionals with bachelor’s degrees.
Machine learning applications: The application of machine learning or AI to perform a specific function in a particular field. This can involve training machines to recognize gestures, detect financial fraud, or analyze the content of ad and marketing campaigns.
Bearing in mind the fact that AI, robotics, and machine learning are still nascent fields, it’s hard to winnow down exactly what someone called an “AI engineer” will do on the job. Knowing how to code is a given. Most early career applicants to this field will boast proficiency in multiple coding languages with substantial knowledge working with computers. Employers also love seeing prospects who have worked with open-source projects so they can see the code they’ve actually written.
Beyond technical skills, the top trait employers are looking for is an innate curiosity and love of AI-related tech and exploring all the options, it can provide. At this point in the game, almost every industry is looking for talent with AI skills.
Rockstars of the AI Engineering World
Andrew Ng: Best known for his joint research with Google and as the former Chief Scientist at Baidu, where he led the company’s AI Group. His research primarily focuses on machine learning and deep learning.
Geoffrey Hinton: A computer scientist and cognitive psychologist, noteworthy for his groundbreaking work on artificial neural networks. He divides his time between working for Google and teaching at the University of Toronto.
Daphne Koller: Israeli-American Professor of Computer Science at Stanford University and one of the founders of Coursera Learning. Her particular area of expertise is machine learning and its application to biomedical sciences as well as Bayesian machine learning.
Yann LeCun: A well-known computer scientist with notable contributions in computer science, machine learning, mobile robotics, and computational neuroscience. He is known for being the first Director of AI Research at Facebook.
Other famous AI engineers along with their contributions:
- Yoshua Bengio (artificial neural networks, deep learning)
- Jürgen Schmidhuber (research in AI, self-driving cars)
- Ian Goodfellow (AI Research Scientist at Google)