How Much Do Machine Learning Engineers Make in 2020
We know many youngsters would be looking to get more insights into the profession and how much do machine learning engineers make in 2020. Check in this blog.
We are living in interesting times, and there’s no doubt about it. I mean who in their right mind have thought that humans and machines would coexist in a way that humans won’t even be able to tell how machines are making their lives easier? Today, machines are outperforming humans in every aspect. They have altered our ways of interacting with other humans, as well as, other machines as well.
Now, that being said, we are in no way under robot invasion right out of a sci-fi movie. Rather the machines that surround us are created and programmed by humans. Yes, today we will be talking about the machine learning engineers; the humans who program and bring life to the machines to perform their own. A machine learning engineer is responsible to program the machines, so it is able to experience, work, and even feel like us.
Now, with so much potential, machine learning engineers are one of the most in-demand professionals in the IT field. According to one report from Jobs and AI Anxiety, which looks at the future of work, and the influence of technology in the job market, the machine learning engineers will be the most sought after professionals. This is in line with the other findings of the report that details that over 30% of the managers reported the use of Artificial Intelligence (AI) and Machine Learning (ML) in their companies, whereas, the other 53% responded that they are looking to incorporate the technology in near future.
Looking at the stats, it is safe to claim that the future belongs to the machine learning engineers and as more businesses and industries explore the potential returns of investing in these disruptive technologies including ML and AI, they can rest assured for a bright and highly in-demand job market.
With such a bright potential, we know many youngsters would be looking to get more insights into the profession and how much do machine engineers make. So, in this blog we have come up with all the relevant details that will help fresh machine learning engineers, as well as, aspiring youngsters to know all about the potential of the profession and how much do machine learning engineers make.
So, let’s start exploring the potential of the profession.
What to Expect in a Machine Learning Engineer Job Description
The machine learning engineer salary will depend directly on his/her job description and roles for which he/she is hired. Now, since it’s still early days for machine learning and there aren’t machine learning engineers available in the industry, thereby, the job description of machine learning engineers will typically resemble that of data scientists, except that there will be a strong emphasis on programming skills.
Contrarily, the job description may also look out for professional programmers and coders with good skills in data management and analysis. Again, the machine learning engineer salary will depend on the job description and the role (junior, senior) he will be hired for.
Here is some prerequisite job description for machine learning engineer:
- Advanced degree (Graduate, Masters) in computer science, mathematics or statistics
- Skills in data modeling and architecture
- Proven programming skills in multiple languages preferably in Python, R or Java
- Basic understanding and experience working with different machine learning frameworks like Keras or TensorFlow
- Advance mathematics skills
- Good communication skills
Machine Learning Engineer Salary in 2020
Since it’s still a fairly young job title with not enough data point to accurately give the range for machine learning engineer salary, we need to make some predictions based out on the salaries from data scientists and software engineers. It’s the right approach to predict how much do machine engineers make because machine learning engineer job description falls within the scope of these two fields. So, here’s a basic structure for machine learning engineer salary in 2020 against various positions:
Big data engineer: The salary would average at $163,250
Data architect: The salary would average at $141,250
Data scientist: The salary would average at $125,250
Data modeler: The salary would average at $101,750
Developer/analyst: The salary would average at $108,500
Software engineer: The salary would average at $125,750
What Does a Machine Learning Engineer Do?
If we are to speak broadly, the job of machine learning engineers is quite similar to some of the other roles in the data science industry like AI engineers, and data scientists. All of these positions involve working with the massive amount of data, needs a strong and polished data management skills, as well as, the ability to develop complex models to solve the problems using the massive data available to them.
However, with these three generic roles, the similarities come to end between machine learning engineers and data scientists. That’s because while data scientists will be developing critical and high-value insights from the data in form of reports or charts with human readability, machine learning engineers will be working to develop complex algorithms and models to enable machines to take over the predictive modeling. They will be using the massive data at their disposal to train the algorithms for specific tasks (that’s where the machine learning stems from), and once the model is trained it will be able to perform the tasks itself without the need for human intervention.
If you haven’t already versed with our routine interaction with a machine learning algorithm, the “recommendation algorithm” used in almost all e-commerce stores including Amazon, eBay, Netflix, and others is the simplest and brightest example of how machine learning algorithms are able to predict our preferences based on our profile and previous interaction with it. Every time you buy or even search a product on these sites, you add data to your profiles, which is then analyzed and processed by the “recommendation algorithm” to give you the most suited recommendations for more products or films you may like to watch. Interestingly, just like humans, the machine learning algorithms don’t stop learning and with each interaction, it continues to improve its accuracy and content value.
Machine learning is quite closely associated with other disruptive data technologies like Artificial Intelligence and Deep Learning. It actually can be said as a subfield of Artificial Intelligence, which is aimed to create intelligent and learning machines. On the other hand, deep learning is also a subfield of artificial intelligence, which is concerned with creating Artificial Neural Networks (ANNs), which are able to understand, analyze and solve multi-layers data sets. Virtual assistants, Chatbots, and driverless cars are some of the practical examples of deep learning.
How to Sharpen Your Saw in Machine Learning Engineer World (Update your Resume)
If we are to analyze the resumes of machine learning engineering aspirants, the most common weak part is the programming experience. This means that if you are seeking a job title of machine learning engineer, you got to have extensive programming experience in multiple languages. Python is especially the most important and most widely used programming language for developing machine learning algorithms, which is why you should get hands-on experience with Python programming. And since it is almost the default programming language for machine learning algorithms (not the default), there are various robust and intensive Python tutorials available online that can help you get experienced with Python language. The other important language for machine learning in R, which is also widely used in the industry. Both Python and R are also relatively easy languages, so you won’t have much difficulty in learning those languages. Other relevant languages for machine learning include Java and/or C++.
Apart from programming skills, you would also like to develop strong skills in dealing with massive data sets. One of the easiest ways to build your data management and analysis skills is to join Kaggle; a Google initiative to help data science aspirants learn the profession by working on data science projects. There are a variety of datasets available at Kaggle, shared by data scientists and machine learning experts from around the world; making it truly a great resource to polish up machine learning skills.
Also, you may wish to take up machine learning courses offered by Amazon – the tech giant and creator of Alex (virtual assistant). Amazon offers a high-value machine learning and certification course which is offered with four pathways including data platform engineer, business decision-maker, and developer and data scientists. Not only these are really great and enriched resources to learn machine learning, but the best part is that Amazon is offered all these courses for free.
Machine Learning Salary for Fresher or Drop Out
When we talk about machine learning fresher, it basically employees with a machine learning engineer with 0 to 4 years of experience. This would typically be a college graduate who has worked around at different companies in data science or machine learning role.
The machine learning engineer salary for fresher will vary broadly depending upon the role, job description, location, and the company. However, the average salary for a machine learning engineer is $97,000 approximately. Couple this with the bonuses and profit-sharing offered by companies and this can rise quickly to as much as $130.000.
Here are some skills that can improve your paycheck as a machine learning engineer:
C++ Programming Language
Big Data Analytics
Natural Language Processing
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Why Machine Learning Engineers are in Demand
As we said above, machine learning is all about leveraging the data to create intelligent machines. And if we are to look at the business models today, it’s highly dependent on data management and analytics. From clients’ interaction to internal systems and processes, businesses need to manage and analyze data effectively to gain a competitive edge over competitors. And in this quest, machine learning is the aptest technology that can help them leverage the full potential of the company’s data.
Here are some of the applications of Machine Learning in the practical business world:
Image and Speech Recognition
Machine learning assists businesses to implement automated systems and procedures to convert unstructured data into useful information like auto-tagging of images, speech to text and text to speech converter, and many other tasks.
as we discussed above, the machine learning algorithms are able to learn the preferences of customers through their previous interactions with the business, thereby, giving them valid, highly-relevant, and targeted recommendations for personalized services.
Risk management and Fraud Prevention
The ability of machine learning algorithms to analyze and process a massive amount of historic data make them perfectly apt to analyze historical records of banks and other financial institutions to make accurate financial predictions, as well as, spot any fraudulent activity in real-time.
How much do machine learning engineers make in California?
The machine learning engineer salary greatly varies depending upon the location of the company. New York and California remain two of the top cities offered the highest salaries for machine learning engineers.
According to statistics, machine learning engineers are offered a 24.4% higher salary in California, as compared to the National average.
How much do Facebook machine learning engineers make?
Facebook is a tech giant and a major player when it comes to the implementation of machine learning algorithms. The social media giant hires hundreds of machine learning engineers with good payout. On average, a machine learning engineer at Facebook takes out $123,395 salary. The salaries can range from $15,000 to $188,000.
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