Data scientists or machine learning researchers work with data and create models that help analyze and interpret data. They must have a deep understanding of programming languages such as Python, Java, and C++, as well as the underlying principles of computer science. This article will discuss machine learning researchers.

Who are Machine Learning Researchers?

  • Engineers specializing in machine learning instruct computers to learn new things without human input. Consider the recommendation engines on some of your favorite on-demand streaming services, online video-sharing websites, and online marketplaces, or the ability of social media applications and platforms to identify spam or unsuitable content on their own.
  • This entails doing a wide variety of things, such as performing basic data science tasks like analyzing data and coming up with use cases, as well as basic data engineering tasks like enforcing data quality and consistency.
  • A significant portion of the role involves working with other stakeholders, such as researchers, data scientists, product managers, and software engineers, to define project objectives, develop strategies, and determine how each professional’s work can contribute to the overall success of the project.
  • Engineers specializing in machine learning compile data, organize it, clean it, and include it with a selected model to derive recommendations based on hidden patterns. The more the program runs, the more it learns about the user and the more accurately it provides answers. 
  • Full-stack development, IT, and data analysis are all necessary skills for machine learning engineers, as companies require versatile programmers to tackle complicated tasks.1

Importance of Learning How to Code for Machine Learning Researchers

  • Learning to code can help develop the required skill set if you want to pursue a career in machine learning. Many machine learning jobs require expertise in programming languages like Python, Javascript, R, or C++.
  • While some aspects of machine learning can be grasped without any coding experience, a solid background in programming languages is essential for any machine learning engineer who hopes to put into practice machine learning models that address practical challenges. 
  • In reality, even rudimentary programming skills will open up opportunities in machine learning by providing access to graphical and scripting ML environments like Orange, Weka, and BigML® that enable you to carry out complex tasks with minimal code.2

Do Machine Learning Researchers Need a Degree?

  • Machine learning engineers often need a bachelor’s or master’s degree in math, computer science, or a related discipline. 
  • To be hired as a machine learning engineer, however, you must show your expertise in the field and your ability to apply that expertise in a variety of real-world contexts.
  • Companies may still hire applicants without a degree if they have relevant experience.
  • Candidates with degrees in unrelated disciplines can often retrain via short courses, online boot camps, or self-study to acquire the necessary expertise and experience to become a machine learning engineer.3

How Can You Get a Job as a Machine Learning Researcher?

  • To facilitate the execution of machine learning, deep learning, and predictive analytics tasks, Google® researchers created an open-source framework known as TensorFlow®.4
  • You can take a single-skill route solely using Tensorflow if you already have a solid foundation in machine learning and have worked on projects in the field but want to brush up on your Tensorflow skills. Tensorflow is a popular tool in machine learning because it simplifies the process of training, testing, and tuning learning models without requiring in-depth knowledge of the underlying math.4
  • Beyond these fundamentals, you should research the specific company and job advertisement to determine if any specialized programming skills are required. You can always take a course in other languages or acquire skills that might be necessary. Training in the company’s preferred technology stack is typically included as a perk of many jobs. 
  • To that end, acquire the necessary foundational knowledge at ease. Figure out how you want to work at it and start. Like your future job as a machine learning engineer, the learning process should be fun.
  • You need to work dedicatedly as a machine learning researcher, as this role calls for both software engineering and data science expertise due to its cross-disciplinary nature.
  • While those with experience in areas like computer science, AI, software development, data science, statistics, or data engineering will have a leg up, it is not uncommon for people to start from nothing and find work in machine learning within a few years.5

Machine learning and AI are still developing. There is a lot to learn and many opportunities for newbies to enter the industry. You need to learn how to code to work as a machine learning researcher. If you liked this article, follow BYJU’s Future School blog for more such content!

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  1. Amidon. (2020, July 5). What is a Full Stack Data Scientist? www. Retrieved November 16, 2022, from
  2. Tavasoli. (2016, December 24). The Importance of Machine Learning for Data Scientists | Simplilearn. Retrieved November 16, 2022, from
  3. University, G. M. (2022). How to Become an AI Engineer or Researcher. How to Become an AI Engineer or Researcher. Retrieved November 16, 2022, from
  4. Vaughan, J. (n.d.). What is TensorFlow? Tech Target. Retrieved 10 November, 2022, from
  5. Violino, B. (2022, April 27). Career roadmap: Machine learning scientist. InfoWorld. Retrieved 10 November, 2022, from

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