is no longer a sci-fi concept, but an actual application of technology we use every day. Machine learning engineers focus on developing computer programs that can access data and use it to learn themselves. Machine learning AI Their daily work involves helping machines learn by creating and fine-tuning training datasets, developing machine learning models, and testing these datasets and models on machines. The goal is for the machine to be able to make informed decisions without the direct instruction of a human. Companies have recognized the value that machine learning can bring to their products and are scooping up people with machine learning expertise faster than schools can educate them. According to , job postings with the terms “machine learning” and “AI” increased by 30% in the last year while people using those terms to job hunt went down by 15%. Indeed This dip in qualified machine learning engineer candidates, combined with an increase in demand for these professionals, ultimately benefits the engineer’s earning potential. In fact, according to the same , the salary for machine learning engineers has increased by 344% since 2015, with the average machine learning engineer making over $145,000 a year. Indeed report Top Companies Need Machine Learning Engineers With code libraries like , , and many more, smaller companies and startups are able to incorporate machine learning into their products. TensorFlow PyTorch While this is a great step on the road to widespread machine learning adoption in the tech industry, most of the groundbreaking work in machine learning tends to happen at big companies. Google is one of the leading companies working on machine learning and artificial intelligence research. Some that Googlers have developed using machine learning include: Google notable projects Flood prediction Earthquake aftershock prediction Developing the open source library TensorFlow A virtual assistant ( ) Google Duplex (in the Pixel 2) Augmented reality In addition to all of the technology that Google has developed using machine learning, they have also paved the way for introducing into space. ethical standards Amazon Ever heard of Amazon Web Services ( )? The cloud computing arm of Amazon is a huge part of its business (check out our on AWS to learn more). Amazon machine learning engineers have developed a huge range of products leveraging artificial intelligence that are available on the cloud. Some of the most interesting machine learning AWS products include: AWS blog post — A service for developers to build, train, and deploy machine learning models at scale. SageMaker — A conversational interface (AKA chatbot).This is what powers Amazon’s Alexa device Lex — Programmable camera with the ability to deep learn (used as a machine learning training tool). DeepLens Apple is another leading company that hires machine learning engineers, with concentrations spanning across five areas: Apple — Build the systems that machine learning researchers work on. Machine Learning Infrastructure — Research supervised and unsupervised learning, game theory, and more. Deep Learning and Reinforcement Learning — Work on Apple products like Siri, text-to-speech, and other NLP technology. Natural Language Processing and Speech Technologies — Develop image-processing software and deep neural networks. Computer Vision — Work on research and development for the latest of Apple’s secret prototypes. Applied Research Facebook Although started out as a fairly simple social media application many years ago, it has grown to become one of the top tech companies in Silicon Valley. Facebook Not only does Facebook use machine learning in their own product to translate languages, fight misinformation, and personalize their user’s timelines, they also are the parent-company for many other products that leverage machine learning, including Oculus VR. Uber It’s no secret that has been developing for the past few years. But that’s only one of the ways that the company incorporates machine learning into their product. Uber has also used machine learning in the following areas: Uber self-driving cars — Uber’s very own machine learning platform that helps developers create, train, and deploy models Michaelangelo User-demand and traffic prediction Driver identity validation Get the Skills to Become a Machine Learning Engineer To become a machine learning engineer, it’s important to have a background in computer science concepts. You’ll need to know how to code and have a solid understanding of algorithms. Once you’ve covered the basics, you can start gaining machine learning skills, like data modelling, quadratic computing, and partial differential equations. Enrol today in Udacity’s Nanodegree to get started on your journey. At 10 hours a week, you can finish the program in as little as three months, while also getting experience working on real-life projects, including a plagiarism detector. Machine Learning START LEARNING

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