Machine Learning

How to Become a Machine Learning Engineer?

Posted in Machine Learning
How to Become a Machine Learning Engineer?

What is Machine learning?

The human neural system learns from their experiences and solves problems through it, so we developed a system that can mimic human behavior and work smartly, and the system is known as Artificial intelligence (AI). AI is a wide range of technology, and machine learning is a subset of this technology, and machine learning is the most demanding system in the present time. The world consists of lots of data, and it is essential to derive the meaning or extract the information from these data. Hence various algorithms are used to do this complex process. These algorithms combine and create machine learning that gives capabilities to the computer to learn new things without being explicitly programmed.

Machine Learning WorkingFigure 1 Machine learning workings

Data and programs are used in input to obtain output in traditional learning, and apart from it, data and previous output are used to get the program and to work in machine learning. Machine learning is creating automated work. A perfect example of this technology is online shopping; in online shopping, if you create your login id in their systems and purchase something from their website, then the website will show similar products whenever you visit that website again. The system provides complete information and searching history of the user to the machine learning system. Then this system extracts the information and learns about the needs of the user.

Future of Machine Learning:

Machine learning has limitless applicability that can change the world and positively impact on various fields like education, computer science, finance, and many more. Currently, machine learning is already applied in critical areas like healthcare to reduce the risks for the patients, finding the issues in the business, and find the loopholes in any process,

This technology will not go anywhere, and it will grow more and more in the future. Hence the demand for machine learning engineers will increase exponentially. The challenges in data are complex, and it requires systems to resolve them, and machine learning engineers will build these systems through their skills.

Who is a machine learning engineer?

As we know that machine learning is the most recent and interesting technology that is rapidly developing and has a vital role in the future, so every company needs specific employees to maintain these systems, these employees are machine learning engineers.

Who is Machine Learning Engineer?

Machine learning engineers are programmers that develop and manage the informative data for the machine learning system. AI is the primary goal of machine learning engineers because the AI system starts the machine learning development process. They are programmers, but their main goal is to go beyond the specific programs so that the programs are enabled to take actions without being explicitly directed to perform tasks in the overall system. According to the latest statistics, there are 1101 vacancies available only in Bengaluru, India. A machine learning engineer is a person full of ideas to use the technology to resolve the issues in the best convenient way possible. ML engineers can work logical and flexible at the same time to mold the current ML frameworks for the different fields.

These engineers are skilled in software engineering and understand the methodology of software development and agile practice to maintain production systems. An ML engineer needs to know about software design and architecture because their primary focus is on creating the data products that work in the production. These engineers can monitor the data products in production and learning. A person cannot become a machine learning engineer if he/she doesn't have the required skill set because machine learning technology needs appropriate skills to handle it and takes the best result possible out of it. Before starting a career as an ML engineer, you need to focus on gaining experience, and there is various way to get experience in the machine learning field, and these ways are:

  • Get a solid knowledge of all aspects regarding machine learning technology.
  • For the theoretical part and official documents of experience, you can take admission in online or offline courses so that you can certify your skillset.
  • Get practical knowledge through real projects on the real data. You can go for Kaggle because it is the best source to have practical knowledge.
  • Most importantly, listen, watch, and read more and more articles and videos available online and take the best knowledge to improve your skills.

The Requirement of a Machine Learning Engineer

There are five crucial requirements which need to be fulfilled by a person to be a machine learning engineer, and they are:

1. Programming Languages

This is an essential requirement because every machine learning engineer needs to have proper knowledge of programming language so that they can work on the different types of data and software related to machine learning. There are bunches of programming languages present in the current technologies, and some of them are Python, C++, and Java. This skill is essential for an engineer because he/she must be able to apply, address, and implement the programming languages with appropriate codings for resolving the issues.

2. Computer Programming

Companies always look for those employees who have great knowledge of computer programming so that they can easily deal with the huge data and manage them. Examples of computer programming are:

  • Data structures (stacks, graphs, multi-dimensional arrays, queues, trees)
  • Algorithms (optimization, sorting, dynamic programming, searching),
  • Computability and complexity (P vs. NP, big-O notation, NP-complete problems, approximate algorithms)
  • Computer architecture (bandwidth, memory, deadlocks, cache, distributed processing).

3. Data Modeling and Processing

A machine learning engineer must know about the data modeling so he/she can easily handle the data for the extraction of information by machine learning techniques. There are few responsibilities of machine learning engineer in case of data modeling process:

  • Finding patterns (correlations, clusters, and eigenvectors)
  • Predicting properties of last unseen instances (classification, anomaly detection, and regression)
  • Error measure process (log-loss for classification)
  • Evaluation strategy (training-testing split).

4. Probability and Statistics

A machine learning engineer can find critical problems in the data through statistics and probabilities because these methods help to extract the information in the best mathematical way possible. Here are some of the process for it:

  • Formal characterization of probability (conditional probability, Bayes' rule, likelihood, independence)
  • Techniques derived from statistics (Bayes Nets, Markov Decision Processes, and Hidden Markov Models)
  • Statistics measures (mean-variance and median)
  • Distributions (uniform, binomial, Poisson and, normal)
  • Analysis methods (ANOVA, hypothesis testing)

5. System Design and Software Engineering

Machine learning engineers work on software that can fit in the broader ecosystem of services and products. It means they have to understand the parts work and communicate using different methods. Machine learning engineers need to use the system design to have a complete machine learning ability for any particular task.

Essential Qualifications of a Machine Learning Engineer

Machine learning qualifications are as similar as the skills of domain experts, data scientists, software engineers, statisticians, and those with a significant amount of knowledge in advanced mathematics and statistical fundamentals that includes an excellent understanding of algorithms.

However, the significant difference is the combination of various technologies and algorithms to provide the best work possible for any organization. Skills that are mentioned below are essential to step up in this field of machine learning and make and boost your career faster. You can go for online courses to learn these skills with the appropriate certification, the required skills are:

  • It is essential to have appropriate experience in machine learning applying methods for the products and features of it.
  • An excellent ability to understand and modify a large number of codes in a convenient manner.
  • A great collaboration and interpersonal skills.
  • A good understanding of algorithms and data structure techniques.
  • Expertise skills in python, C, and C++ development is required.
  • An excellent understanding of NLP, computer vision, multimodal fusion, ASR, and deep learning.

Top Machine Learning Tools

There are different tools for machine learning that are essential for an engineer to learn and master into it for getting the best job possible in the Machine learning field, these tools are:

  • Scikit-Learn
  • KNIME
  • TensorFlow
  • WEKA
  • Torch / Pytorch
  • RapidMiner
  • Azure Machine Learning Studio
  • Google Cloud AutoML
  • Accord.NET
  • COLAB

Job Roles of the Machine Learning Engineer

  • Machine learning engineer has to study and transform data science prototypes
  • Design a new machine learning system
  • Research and implement the right ML tools and algorithms
  • Develop and mold machine learning applications according to the needs
  • Select and use proper data representations and dataset methods
  • Perform statistical analytics, tests, experiments and fine-tuning using various test results
  • Extend the present ML frameworks and libraries
  • Keep abreast of developments in the field.

Conclusion

Machine learning is a technology used in an extensive range, and this technology has enormous scope in the future. Hence, it requires various skills and responsibilities to handle technology in a very effective manner. This article holds complete acknowledgement of machine learning and machine learning engineers and lacked qualities to get hired in any company because there is a significant amount of scope in companies like Facebook, LinkedIn, and IBM, etc. Machine learning is not the most robust path to walk on. You have to be aware and well skilled at the same to conquer every issue in the datasets to provide the best results through the machine learning technology, and you will surely get success.

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Simran Kaur Arora

Simran Kaur Arora

Simran works at Hackr as a technical writer. The graduate in MS Computer Science from the well known CS hub, aka Silicon Valley, is also an editor of the website. She enjoys writing about any tech topic, including programming, algorithms, cloud, data science, and AI. Traveling, sketching, and gardening are the hobbies that interest her. View all posts by the Author

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