Top Skills Required for Machine Learning Engineers to Know in 2021
Global Tech Outlook outlines the top skills for machine learning engineers
Since the emergence of cutting-edge technologies such as artificial intelligence and machine learning, there is a huge demand for machine learning engineers from reputed tech companies across the world. This job profile offers lucrative salary packages with high skills for machine learning engineers. The popularity of working with machine learning algorithms has skyrocketed in these recent years to build smart machines and models to boost productivity in multiple industries. Let’s explore some of the top skills for machine learning engineers that need to have in 2021.
Top skills for machine learning engineers
Computer science skills: Machine learning engineer’s need to possess some skills in the domain of computer science including basic fundamentals such as writing machine learning algorithms, computer architecture such as memory, cache, distributed processing, machine learning libraries, data structures like a queue, graph, tree, and many more. A Bachelor’s degree in computer science can help to gain computer science skills with in-depth knowledge.
Data science skills: It is essential for machine learning engineers to know data science skills to work with different types of data as well as familiarity with any popular programming language like Python, Java, and many more. Tech companies need to develop evaluation strategies for artificial intelligence and machine learning algorithms efficiently. Data science skills also include data modeling and evaluation with machine learning algorithms depending on the type of structured, unstructured, and semi-structured real-time data from reliable sources. It is needed to use the existing errors such as log-loss for classification, logarithmic loss, mean absolute error, mean squared error, etc. to tweak the model like back propagation for neural networks, and many more. A machine learning engineer should have a better understanding of classification accuracy, confusion matrix, F1 score, and so on for better performance in a tech company.
Basic machine learning skills: Machine learning engineer’s must have some basic machine learning skills through their years of hands-on experience in tech companies. These skills may include optimization of machine learning algorithms such as K Means clustering, Apriori algorithm, decision trees, linear regression, dynamic programming, neural network architecture, NLP, deep learning, and many more. Machine learning library includes Scikit learn, Spark MLlib, TensorFlow, Hadoop, and many more. Machine learning engineer’s need to apply one of these on suitable models efficiently and effectively.
Problem-solving skills: Problem-solving skill is one of the important skills to possess in any machine learning engineer. They need to have a strong ability to solve complicated and real-life problems within a short span of time by removing all kinds of barriers efficiently and effectively. They are required to develop solutions as soon as possible to prevent a massive loss for a tech company.
Mathematical skills: Mathematical skills include different concepts such as linear algebra, probability theory and statistics, multivariable calculus, algorithms and optimization, as well as other mathematical concepts. This skill plays an important role in the professional career of a machine learning engineer to select the right algorithm for the needs of a tech company, strong understanding of the parameters, deciding the validation strategies, and many more functionalities.
