If you’re at all keyed into artificial intelligence (AI) and machine learning (ML) concepts, chances are that you’ve heard of deep learning. It’s a fascinating topic, branching off of regular ML and delving into neural networks that attempt to mimic the way the human brain works. With deep learning, machines can practice unsupervised learning and figure out how to make decisions without direct guidance from a human.
Deep learning has huge implications for futuristic tech, including natural language processing (NLP), computer vision, and bioinformatics. In fact, graduates from Udacity Nanodegree programs have used deep learning out in the real world to innovate in the healthcare sector for COVID-19 and unearth patterns in ancient Turkish art.
Not only is the field of machine learning (and more specifically, deep learning) overwhelmingly fascinating, it’s also growing faster than almost any other job field. According to an Indeed Job Report from 2019, the number of machine learning engineer roles increased by 344% between 2015-2018. The average base salary for a machine learning engineer is already a whopping $146,000+, but if you spend the time to study the niche of deep learning, the average base salary increases to almost $180,000 a year.
What Companies are Hiring Deep Learning Engineers?
At this point, after seeing the job growth, base salary, and intriguing breadth of work for a deep learning engineer, you might be wondering what kind of companies are hiring for this role. You’re in luck! We’ve put together a short list of the best companies hiring deep learning engineers in 2020.
Have you ever played a video game on your computer? You can thank NVIDIA, the inventor of graphics processing units (GPUs) for that. NVIDIA is an OG Silicon Valley tech company that has been around since 1993. Since 2014, they’ve expanded their company to focus not only on gaming and graphics, but also on a number of emerging technologies, including AI.
With well over 150 deep learning and AI engineering roles currently available in the US, it’s safe to say they’re heavily invested in finding great ML engineers. An excerpt from one of the Senior Deep Learning Software Engineer roles says “You will be responsible for research, development and deployment of DL based solutions for building conversational AI systems – building Speech, Computer Vision and Multi-modal interaction models.”
Lawrence Berkeley National Laboratory
Is being a deep learning engineer akin to being a mad scientist? Maybe. The Lawrence Berkeley National Laboratory (or Berkeley Lab, for short) is a lab snuggled into the Berkeley hills that mainly conducts research for the U.S. Department of Energy (DoE). One of the most notable accomplishments of the lab is the discovery of dark energy.
Deep learning (part of the lab’s Computational Research Division) plays a huge role in the daily workings of the Berkeley Lab, displayed by over 150 current ML-related job openings. After taking a peek into a few of their job descriptions, it’s clear that they want someone to eat, sleep, and breathe deep learning. In a deep learning role at the lab, you will be expected to analyze performance and scalability for deep learning on supercomputers, create and optimize algorithms for deep learning, and even publish research papers about your findings.
Oh, Apple. Don’t we all know you well. Originally founded in 1976, Apple has ballooned to become one of the most infamous companies in Silicon Valley. Creator of the iPod, iPhone, and all of their proprietary cables. These days, Apple has a bit more competition from competitors like Google and Android. To stay relevant, they aggressively hire the best ML engineers they can get their hands on.
Currently, there are almost 200 open roles for the keyword “deep learning” on Apple’s website. The jobs range from research to firmware, compiler to graphics. Apple is secretive when it comes to the daily work of their engineers, but to borrow from a job description, a deep learning engineer will “work in a small and dynamic team to design and implement cutting edge computer vision algorithms for Apple products.”
How Do You Become a Deep Learning Engineer?
To become a deep learning engineer, you need a background in computer science fundamentals, machine learning and AI, statistics, and mathematics. Coding and data analytics are a big part of the job, so a thorough understanding of programming languages like Python, C++, R, and Matlab are key.
Enroll in our Deep Learning Nanodegree program today to get started on your path to becoming a deep learning engineer. At 12 hours a week, you can complete the program in just four months, while adding a collection of projects to your portfolio.