With 82% of companies requiring Machine learning engineers, choosing it as a career choice is among the wise decisions. Regardless of one’s previous study and job background, career transition in the field has brought forward successful results. Working hard to gain proficiency in skills and gaining hands-on experience on projects is the gateway to opportunity in the field. Moreover, coupling it with a well-polished resume strengthens your chance of clearing the first stage of selection, followed by a test or interview where candidates are expected to exhibit their possession of knowledge and experience.
Learn in detail about the potential of a machine learning career, the necessary skills, the roadmap and more.
Here’s what we’ll cover in this article:
What do Experts Say?
“Machine intelligence is the last invention that humanity will ever need to make. With data collection, 'the sooner, the better' is always the best answer.”
~ Marissa Mayer
Former President and CEO at Yahoo
Careers in computer-based courses, with a focus on Machine Learning, offer a promising option to aspirants. With a global surge in demand for AI-driven solutions, ML careers offer room to exhibit skills and innovate. Machine Learning presents a myriad of opportunities because of the following:
The important skills for Machine Learning are as follows.
As stated previously, Machine Learning encompasses wide scope for the aspirants. The job outlook has been promising from top experts in the industry. The World Economic Forum’s Future of Jobs Report 2023 states that the Demand for AI and Machine Learning Specialists is expected to grow by 40% or 1 million jobs. Interested candidates can choose from the following famous career paths:
Thinking about beginning a career in Machine learning from any background through domain change is the common approach owing to the AI revolution. With people switching to the technical background, the most important thing is the will to learn and keep upgrading with technological advancements. Currently, educational platforms offer hybrid learning models at one’s preferable time to aid in switching careers. The path to machine learning success can be summarized as follows:
Basic clarity in concepts of computers, programming languages and mathematics is one of the basic needs to become a machine learning engineer. A Bachelor’s degree acts as a stepping stone. However, career transition through introductory courses is also possible.
Programming language is the base of work in software and machine learning engineering. The ideal candidate is expected to possess excellent familiarity with a good portfolio of languages like Python, R, C++ or Java. Working knowledge or proficiency to deal with real-life challenges is one of the key skills desired by the companies.
Understanding of concepts like supervised, unsupervised and deep learning. Model evaluation, bias and fairness and similar others find daily usage in machine learning jobs. Similarly, tools like Jupyter Notebooks, TensorFlow, PyTorch, scikit-learn, Keras and Pandas are equally popular requirements.
Alt-text: Important tools for Machine Learning
Look for experience through internships, entry-level jobs or collaboration under projects. Get familiar with skills, programming languages, concepts and tools through real-world projects. Learn about the functionality of projects and the tasks performed at the basic level. Use the same to design projects yourself.
With concept clarity of basics, candidates can opt for certification courses from software developer companies like Microsoft or Google. Clear the exam and apply for the job requiring proficiency in the tools you opted for. It enhances the chances of landing the job owing to certified proof of the presence of required skills and knowledge.
Increase connections with people from the field through interactions via workshops, conferences and events. Connect with professionals and look for opportunities to work under them or simply assist them in their projects. Networking offers excellent opportunities to get along with more other people in the field who can offer better possibilities for a career based on one’s skills. Additionally, you can participate in contests to exhibit your skills.
Develop something unique in yourself and state the same to the recruiter. Besides, here are some key techniques for an impactful machine learning profile:
Consider a well-polished machine learning resume below for your reference.
Understand your knowledge about computers, programming languages, mathematics and currently trending tools. Build your knowledge base and application skills to start a career in machine learning.
Begin with analyzing your skillset and accordingly gaining knowledge and experience in foundational requirements of Machine Learning. Follow it up with certified courses and internships to gain experience.
The time varies based on one’s educational background, time invested in learning and ability to learn. An online course offering a brush-up on basics and interview preparation can prepare a candidate familiar with concepts in 2 to 4 months through Interview Kickstart.
Top companies looking for Machine learning engineers and related positions can be your next stop if you aim for them. Helping you through the preparatory stage, Interview Kickstart aims to guide and help you revise every crucial detail pertaining to machine learning. Assisting in the journey, our promising expert-designed mock interviews and learning modules have placed numerous students in brands like Amazon, Google, Microsoft and many more. Begin your journey to becoming a Machine Learning engineer now!