Your guide to cut through the AI HYPE! Part 1- Becoming a Machine Learning Engineer.
If you’re looking to cut through the AI hype, you have to reserve a place for yourself in one of the AI positions.
You can read about Job Functions in Data Science and Machine Learning in this article and choose the best place for you!
Let’s start with one of the most exciting and important roles in AI , a Machine Learning Engineer!
In order to find out what is expected of us as Machine Learning Engineers, We’ve analyzed a lot of Machine Learning engineer job postings!
There is a lot of confusion in the job market. So, Let’s see what the data can tell us.
1- Starting with Education..
One of the most common question among job seekers in Machine Learning Engineering is, “What is the most sought-after educational background?”, “What are the degrees and fields of study required to become a Machine Learning engineer?”
“ A Bachelor’s degree is often required while a Master’s/Ph.D is preferred. “
According to data in the job market:
• The most required academic degree is a Master’s degree.
• There are about as many job postings looking for a PhD as there are for a Master’s degree.
• Bachelor’s degree is the last on the ranking, yet it also has a large number of opportunities.
It is worth mentioning that there is a lot of flexibility in the most of job postings in terms of the type of degree. Whereas, a bachelor’s is often required while a Master’s/Ph.D is preferred.
There are also great opportunities for holders of specialization degrees!
It seems that Computer Science, with Statistics and Mathematics as the third place are the three specializations employers are searching for. Followed by Electrical engineering and physics degrees.
2- Where is the largest presence of job openings?
Next in our study, we analyzed the companies with the highest Machine Learning job openings.
As expected, the top 10 companies are the most exciting firms in tech field. Those who rely extensively on machine learning to run their platforms.
Leading undisputedly by Apple at the top of the list, followed by Twitter, Amazon, Facebook, Snapchat, and TikTok.
With regard to the size of the company, Unsurprisingly, there are more postings in
the large corporations with with over 10,000 employees.
There are also a significant number of job offers from both mid-sized businesses (1000 to 10,000 employees) and smaller businesses (with less than 500 employees).
“ Leading by Apple at the top of the list, Followed by Twitter, Amazon, Facebook, Snapchat, and TikTok. ”
3- Let’s take a look at the industries with the highest job openings for Machine Learning Engineer.
It is obvious that the majority of the offers are coming from the IT and Wholesale/Retail industries.
However, still there are a numerous offers in the Finance , Education, and Consulting industries.
4- Working Experience!
Next in our study, we analyzed one of the crucial factors to get this lucrative job,
Working Experience:
Based on our data, the majority of machine learning offers are for people with (1–5) years of relevant experience.
More general speaking, there are a good number of offers for people with at least 2 years of experience. While there seem to be fewer offers for freshers or for 5+ years-of-experience candidates.
5- Experience required in relation to Degrees:
Okay! Now let’s pay attention to the experience factor in relation to degrees. For holders of a Bachelor’s degree, the required experience is an average of 4 years, while the experience required with a Master’s degree is roughly one year less – 3 years. As for holders of a PhD, they need 2 years of experience.
And that’s certainly good news for those of you who have a Bachelor’s degree with a few years of valuable experience. This provides you with a pretty good opportunity with ML employers!
6- The Practical Part of ML!
Alright! This gives us an idea about the expertise needed for ML Engineers. Let’s take a look at the most practical part of securing an ML engineering job – the required skillset, shall we?
According to what the data tells us, to be a Machine learning engineer,
No surprise here – Machine learning is the most relevant skill required.
But that’s not all! Most of the job postings have listed Deep learning and its fields like Computer Vision and Natural Language Processing (NLP) as a requirement.
There was also much mention of the Big Data, Data visualization, Data analytics and Statistical modeling. In addition, deployment tools like Docker and version control tools like Git are mentioned in quite a few jobs, as well.
Continuing with the most sought-after skills, First off – Programming Languages.
Obviously, Python is the primary Language required.
In addition, Java and C++ are listed more often than R.
SQL have been requested in quite a few descriptions, too.
Dig deep into each type of the necessary skill. What about Deep Learning Frameworks:
Tensorflow side by side with Pytorch are, definitely leading our results as the top two frameworks. Followed by Keras and Caffe.
Working with a variety of packages to handle the different ML tasks can be an critical skill for any ML engineer.
Scikit-learn tops the list, with Pandas, Numpy and Scipy following in its footprints.
” Machine learning is the most relevant skill required.
With Python is the primary Language. “
Okay. let’s examine the most frequently requested Big Data Technologies:
Spark is listed as the top, followed by Hadoop. While Kafka and Hive seem to be mentioned in fewer job offers.
What about the Cloud Technologies?
AWS tops the list the moment. Followed by Google’s GCP and Microsoft’s Azure.
In terms of Data Visualization Skills, It’s not really important for an ML Engineer. There’s just a few mentions of its tools. Like Tableau and Power BI have mentioned just a few dozen times.
The paradox, according to what the data tells us, is that communication skills, along with technical skills, seem just as important!
220 Postings have a mention of communication skills as a definite requirement for the desired worker.
So, today we have answerd the most common questions every Machine learning Engineering job seeker needs to know. And you found the solutions you need to put you on the path to getting an ML job.
Now try to solve the real-world problem by combining all the skills you learned with us today with the time and effort required to get a more real-life-like experience, and be ready to upgrade yourself every day!
If you have any doubts or suggestions, feel free to leave them in the comments.
We are happy to help.
Cheers!