Machine learning is the study of algorithms. In this study, they learn about the data models that computer systems utilize to perform specific tasks. In simple words, machine learning is all about making computers to perform intelligent tasks without explicitly coding.
The machine learning is a new and rapidly booming industry. There are many reasons to learn machine learning and many job opportunities which are increasing day by day. The machine learning is a very big industry and the demand for the machine learning engineer is also increasing. You can also try to think about this field to get a good job.
In this article, I will talk about the various doubts people have about the Machine Learning Engineer.
There are various types of work that a machine learning engineer needs to complete. These works are the main work in which
An algorithm is a finite sequence of well defined, computer implementable instruction to perform a computation. A machine learning engineer is someone who develops and implements production-ready algorithms and methods. Machine learning engineers will design, implement and ship new algorithms.
It also co-develops machine learning solutions with data scientists and engineers. Create and maintain machine learning solutions to solve business problems
Machine learning engineers also provide technical guidance for performing other functions in a company. Provides technical guidance to product teams on the choice of machine learning approaches appropriate for a task. It means that they are one of the main parts of a company. As without them, the other functions will stop working.
A machine learning engineer also provides architectural guidance. Provides architectural guidance on changing prototypes to high-performance production models.
They also provide feedback to other parts of the company. Provides feedback on tools and new features required to send it back to the development teams. As after getting the feedback from the machine learning engineer the development team and work on the next step. Optimizes the machine learning solutions for performance and scalability. It is also a very important part of the whole process for a company.
Contributes to cutting edge research in Artificial Intelligence and machine learning. They have great knowledge about AI and machine learning and helps in the same. This way they are the most important part of the company.
They not only work in the IT part but also contributes to the business problems. Solves business problems like reducing customer churn, running targeted marketing. They have overall responsibility for running a business as their skills and guidance is very necessary for a company.
Here are a few skills of machine learning engineer
Knowledge of Math contributes very much to the whole IT sector. It is also necessary for the Machine learning field. The knowledge of math such as probability and statistics, linear algebra and calculus.
Programming skills are also important as it defines the relationship, semantics, and grammar which allows the programmers to effectively communicate with the machines. A little bit of knowledge of coding skills is enough. But it’s preferred to know data structures, algorithms and oops concepts.
The main programming languages you need to learn are Python, R., Java, and C++. It is preferred to master any one programming language. But it is advisable to have a little understanding of other languages and what their advantages and disadvantages are over your preferred one.
The skills of data engineers are also required. It mainly is the Ability to work with a large amount of data. It also includes Data processing, knowledge of SQL and NoSQL. ETL (Extract transform and load) operations, data analysis and visualization skills.
Some of the other skills of data engineer are coding, machine learning, data warehousing, Etc. All these skills are referred to as data engineer skills.
We should be familiar with popular machine learning algorithms such as linear regression, logistic regression, decision trees. Random forest, clustering, reinforcement learning, and neural networks are some of the machine learning algorithms.
You can learn both the theory and implementation of these algorithms in R and Python.
The machine learning framework is an interface, library or tool which allows developers to build machine learning models easily, without getting into the depth of the underlying algorithms.
You should be familiar with popular machine learning frameworks such as sci-kit learn, tensor flow, azure, Caffe, Theano, spark, and torch.
As the demand for the machine learning engineer is increasing it means that there is some hike in their salary too. They are provided an equitable salary according to their work is done. It has also outpaced other technology jobs. There is an approximately 344% increase since 2015.
The entry-level ML engineer’s salary is generally lower than the other levels. The annual salary of the Machine learning engineer salary is $76,953 – $151,779. It is generally a very high amount.
The Entry-level ML engineer also receives a bonus. The amount of bonus depends upon the level of work done by them. As a machine learning engineer plays a very important role in the company so the bonus given to them is also high. The bonus can be varying from $2,974 – $25,541.
The very interesting thing about the Machine learning engineer is that they also get a share in the profit of a company. The amount of profit depends on the size of the company. It can range in $1934 – $51,285. This is a part of entry-level machine learning engineer salary
The total pays a machine learning engineer receives including the salary, bonus, profit-sharing, and other perks are from $80,184 – $162, 727. Total pay includes everything from machine learning engineer salary to bonus and profits as well.
The Salary received by a middle-level ML engineer is generally high than that of Entry-level ML engineer. The middle level can receive $133K Annually.
The salary of a senior-level is more than both the entry-level as well as the middle level. The amount of salary they can get is 181K Annually which is a very large amount. It is only because of the demand for machine-level engineers around the world.
The ML engineer receives a very good amount of salary as you can see above discussed in the article. A machine learning engineer salary is more than your assumptions. They will be able to afford a good lifestyle after becoming an ML engineer.
An ML engineer holds a very reputed position in a company. All the decisions related to the AI will be taken after your feedback which is a very praiseworthy thing. You will also get a good environment in the office to work with your colleagues. And some other opinions are also taken from you.
Other than salary, there are also some attractive perks are available for an ML engineer. Such as bonuses, profit sharing, etc. and these are in a very big amount. All these benefits consistently make this job very demanded.
There is also a disadvantage in this job as everything as its both positive and negative sides. So, the negative thing in this field is:
The study of this job is very difficult. As you need to have a strong base in mathematics and you need to learn many other skills also. The skills are Programming, data processing, ML frameworks, ML algorithms, Etc. All these skills increase the difficulty level of this field. You need to gain mastery in various fields only then you can become a machine learning engineer.
Conclusion
So, it is concluded that machine learning is spreading around the world. If you are thinking about doing the Machine learning then you should surely pursue this. As there is a very great scope for this in the future.
There can be also many questions people have about the machine learning engineer salary and its field. Some of the very common questions are:
Also, Read Reasons to Learn Machine Learning
A clean and sanitized environment is vital to health care and lab ecosystems. Contaminants like dust, particles, debris, bacteria, viruses…
Artificial intelligence is increasing in various sectors, including photonics. AI enthusiasts in multiple fields are excited to see how its…
Automation is rising across all manners of manufacturing workflows. However, in many cases, robotics solutions can go further. Workholding is…
Accurate documentation of diagnoses, treatment histories, and personal health information are all crucial in delivering quality care and ensuring patient…
Material-handling activities can be dangerous because they require repetitive tasks that may cause strain or injuries. Additionally, employees must learn…
AI enthusiasts in all sectors are finding creative ways to implement artificial intelligence’s predictive analytics and modelling capabilities to mitigate…