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Top Machine Learning Jobs to Choose in 2022

Machine Learning Jobs

With the spontaneous evolution of technology, the role of machine learning is also emerging drastically across different verticals. The advent and growth of machine learning have enhanced our standard of living ever since, and machine learning has become a part of our daily actions and events. Right from search engines to smart home devices, from smartwatches to online e-commerce apps – everything uses machine learning to deliver better services with more and more experience. According to Million Insights’ prediction, the machine learning market will grow to USD 96.7 billion by 2025. That makes a CAGR of 43.8 percent from 2019 to 2025. This article will discuss the top machine learning jobs to pick in 2022.

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Top Machine Learning Jobs in 2022

Almost all companies are trying to leverage the potential of machine learning. New jobs roles and positions are opening up in nearly all organizations. Let us now explore some of the most impressive machine learning jobs one can choose in 2022.

  • ML Software Engineer: They are software developers who work in artificial intelligence, explicitly with machine learning (ML) software development projects. Machine learning software engineers are responsible for creating and enabling ML models to identify input information and understand the relationship between various events within the app. Such a job profile demands exceptional analytical, logical, and programming skills. Aspirants should be able to write well-structured code in one or more programming languages like Python, C++, JavaScript, etc., along with tools like Spark, Flink, Kafka, etc. Professionals or aspirants with a bachelor’s degree (computer science, mathematics, etc.) and two years of ML project development experience usually apply for this job. A Machine learning Engineer earns an average salary of USD 112,266 annually.
  • ML Cloud Architect: Cloud computing has also become well-acquainted technology that provides computation, storage, and other services over the internet. The cloud architects are responsible for overseeing cloud computing strategies and cloud-related operations within the enterprise. Machine learning cloud architects are unique job roles where the cloud architects have to implement machine learning algorithms to cloud platforms, servers, storage, etc. They implant ML algorithms so that cloud technology can understand and relearn customer traction, behavior, and users’ system requirement. Professionals and aspirants should have experience (1-2 years) designing architectural systems in Azure, Google Cloud, & AWS, along with configuration management toolkits like Chef, Ansible, Puppet, etc. It is also essential to have proficiency in programming languages like Python, Go, etc. Professionals or aspirants with a bachelor’s degree (computer science, mathematics, etc.) with cloud certifications of AWS, Azure, or GCP will be an added advantage. A machine learning cloud architect earns an average salary of USD 129,000 annually.
  • Machine Learning Scientist: Machine learning scientists are responsible for building models and presenting efficient results. They remain focused on integrating software engineering with machine learning models & perform intense research to bring compelling solutions to the project. They often work as a part of the research and development (R&D) department. Such a role requires knowledge of multiple disciplines such as artificial intelligence, deep learning, neural networks, computer vision, NLP, programming efficiency, quality assurance, etc. Professionals or aspirants with a master’s degree (computer science, mathematics, etc.) or Ph.D. with two years of ML project development experience can apply. A machine learning scientist earns an average salary of USD 1,37,053
  • Computational Linguists: A specialized domain that requires intense machine learning (ML) and Natural Language Processing (NLP) tasks to make a computer understand and interact with humans. In this job role, professionals are responsible for developing algorithms that support building apps like online dictionaries, translating systems, virtual assistants, intelligent chatbots, robots, etc. They require deep knowledge of parsing human languages to machine-understandable format through NLP and Artificial Neural Networks (ANN). Professionals and aspirants need to have sound knowledge of Python & other scripting languages along with mathematics, analytics, deep learning (DL), and other frameworks used in ML and DL. Professionals or aspirants with a master’s degree (computer science, engineering, robotics, etc.) can opt for this role. A computational linguist earns an average salary of USD 91,635
  • ML Cybersecurity engineer: Machine learning cybersecurity engineers are responsible for creating customized security solutions for companies or the organization where they get hired. They develop threat detection and attack classification solutions that automatically identify attack vectors, threat patterns, and behavior. Already, products like Gmail and browsers like Chrome and Firefox use machine learning to identify spam, phishing links, XSS and CSRF attacks, etc. ML also helps in creating robust network security. They leverage previous cyber attack datasets for determining the different scopes of networks prone to particular attacks. Many companies hire cybersecurity engineers and train them with advanced machine learning skills to help them create customized ML applications. Professionals or aspirants with a bachelor’s degree (computer science, mathematics, etc.) and proficiency or certification in cybersecurity and machine learning can opt for this role. An ML cybersecurity engineer earns an average salary of USD 101,548 annually.
  • AIOps Engineer: Artificial Intelligence for IT Operations is another significant job role where the professional involves creating and deploying ML algorithms for improving IT operations and analyzing data. Most large and mid-sized firms spend a lot on different IT and other business operations like real-time analytics and business performance. They reduce the labor and operational costs to a significant level. They use machine learning models and train them using past business operation datasets to build such automated and self-learning algorithms for efficient IT operations. Professionals or aspirants with a bachelor’s degree (computer science, mathematics, etc.) and proficiency or certification in networking or cloud technologies with machine learning can apply for this role. An AIOps engineer earns an average salary of USD 30,000 (approx)

We hope this article has given you a crisp idea of the different machine learning job profiles that one can choose as their career in 2022. Today, almost all sectors and firms like healthcare, finance, IT, marketing, manufacturing, etc., hire machine learning experts to make their systems automated, efficient and respond to operations with more intelligence. If you are a novice yet have a soft spot for machine learning and want to improve your skills online, we suggest you visit Jooble to find a machine learning intern remote job.

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