How to become a Machine Learning Engineer
Becoming a Machine Learning Engineer is an in-demand career
path. It
requires deep expertise in Machine Learning and a
strong network to carry you along. Here are some resources to help you on your journey.
Browse
Machine Learning
experts
Why should you become a
Machine Learning Engineer?
Demand for experts in Machine Learning is growing rapidly. Companies are
looking for people with deep expertise in the field of Machine Learning to help
them
build their products and services.
As a result, Machine Learning Engineers are in high demand and command high salaries. According to leading
sources,
the median salary for a Machine Learning Engineer is $150,000 and a
senior Machine Learning Engineer can earn up to $200,000. Even entry-level
positions can command great salaries.
No wonder that interest in a career in Machine Learning is growing rapidly.
Explore the
resources below to learn more about how to become a Machine Learning Engineer.
The Machine Learning must-reads you shouldn't miss.
Key articles and posts of industry experts can help you get a better
picture of what you are getting into.
In our opinion, these are some must-reads you really shouldn't
miss.
Karpathy on "Software 2.0"
Andrej Karpathy is the Director of AI at Tesla. Before that, though, he authored this blog post in 2017 talking about Deep Learning as "Software 2.0" of some sort. A must-read if you ever want to have another way of thinking about ML.
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Simple Reinforcement Learning with Tensorflow
This 8-part series by Arthur Juliani (Deep RL researcher at Unity) is an amazing entry point to the new and mysterious advancements of Reinforcement Learning, perfectly suited for folks coming from other topics in Machine Learning.
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Building Safe A.I. (Trask)
Andrew Trask is a specialist in Federated Learning and Safe AI. In this blogpost, he writes about training a neural network that is fully encrypted during training (trained on unencrypted data).
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Opportunities and projects in the Machine Learning
space.
In the end, advancing your career is all about getting the right
opportunities at the right time and
a
good portion of luck.
These are some interesting things going on in
the Machine Learning space and you
probably don't want to miss them.
Specialize with Kaggle
It wouldn't be the first time I've seen someone get hired over good Kaggle results! Kaggle competitions are data science and ML projects that are graded through a public leaderboard. A good place on the leaderboard shows that you know your craft and can apply your knowledge to real-life problems!
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Find early stage positions
While Google & co. are saturated with academic talent, there are incredible opportunities to get your foot in the door quicker with an early-stage positions.
Today, startups and early-stage businesses are looking for ML engineers more and more for a wider variety of jobs than what's possible in the more established industry.
Platforms like AngelList can help you find those positions!
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Get into open-source
The world thrives on open-source software and this is no exception. Core contributors to core libraries and fast-growing tech like React, scikit-learn, Bitcoin and TensorFlow prove their abilities by going into the inner workings of a framework to improve it. For many companies, that's a desirable skill!
These projects are always looking for fresh faces. Grab an issue from the issue board or review a PR to get started!
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