Want to become an Azure AI Engineer? Check out this detailed Azure AI salary guide to understand how much you can make as an AI engineer. Azure AI is a robust framework for developing machine learning, conversational AI, data analytics, robotics, IoT, and more.
Azure AI platform allows you to enhance your project in a variety of ways, from better application creation, data analysis, or machine learning capabilities.
Microsoft Azure offers a spread of services designed to work together to enable rapid development of high-performance AI solutions.
There are so many different ways for Azure AI to help enhance your work and many customizable options to tailor these services to your needs. The demand for AI-related job roles is increasing at an unbelievably faster rate. Therefore, the demand for an Azure AI engineer is also at an all-time high.
I will be unveiling all you need to know about Azure AI engineer salary.
Who is an Azure AI Engineer?
Azure AI engineers build, manage, and deploy AI solutions that leverage Azure Cognitive Services and Azure Applied AI services. An AI Engineer’s primary responsibilities include analyzing AI demands and developing AI solutions.
Azure AI Engineers collaborate with solution architects to communicate their vision and construct entire end-to-end AI solutions alongside data scientists, data engineers, IoT specialists, and AI developers.
AI engineers make recommendations for appropriate technologies and tools for solution design. Furthermore, the AI engineer is in charge of implementing solutions that meet performance and scalability requirements.
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Azure AI Engineer Salary In 2023
Azure AI Engineer Salary In US
As of July 2023, the average annual pay for an Azure AI Engineer in the United States is $145,348 a year. This is approximately $69.97 an hour which is the equivalent of $2,796/week or $12,112/month. Entry level positions start at $120,855 per year while most experienced workers make up to $209,270 per year.
Average Azure AI Engineer Salary by State In the US
|State||Annual Salary||Monthly Pay||Weekly Pay||Hourly Wage|
Highest Paying States for Azure Ai Engineer Jobs in the U.S.
Here are ten states where the typical salary for an Azure Ai Engineer job is above the national average.
- New York
- New Hampshire
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Azure AI Engineer Salary In UK
The average Azure AI engineer salary in the United Kingdom is £60,000 per year or £30.77 per hour. Entry level positions start at £50,000 per year while most experienced workers make up to £80,000 per year.
Azure AI Engineer Salary In Canada
The average Azure AI engineer salary in Canada is $111,250 per year or $57.05 per hour. Entry-level positions start at $97,500 per year, while most experienced workers make up to $125,000 per year.
Azure AI Engineer Salary In India
The average Azure AI engineer salary in India is 8 lakhs per year. Entry-level positions start at 5 lakhs per year, while most experienced workers make up to 5 lakhs per year.
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How to become Azure AI Engineer?
To be able to make money as an Azure AI engineer you need to first become an Azure AI engineer and the most significant aspect of this journey will be the development of abilities and a thorough comprehension of the concepts. However, there’s no need to be alarmed.
Here is a step by step process on how to become an Azure AI Engineer for both beginners and experts.
1. Getting Microsoft Certified
Your first step is to be certified by Microsoft. The certification for the job role of Azure AI engineer is one of the important aspects. You will have to clear one certification exam that tests the capabilities of Azure AI engineers.
The certification exam helps you obtain the tag of Microsoft Certified Azure AI Engineer Associate. The certification exam has the code AI-100 and is known as “Designing and Implementing an Azure AI Solution.”
The exam is ideal for AI engineers interested in the development of AI solutions with a thorough evaluation of requirements for AI solutions and recommending appropriate tools and technologies for the same.
The certification exam tests the abilities of candidates in architecting and implementing AI solutions that involve natural language processing, bots, computer vision, agents, and speech.
Knowledge requirement for the exam:
- Firstly, you must learn C# or Python in order to pass this exam.
- Secondly, you must be able to create computer vision, natural language processing, knowledge mining, and conversational AI applications on Azure using REST-based APIs and SDKs.
- It’s essential to comprehend the components that make up the Azure AI portfolio, as well as the data storage solutions offered. Furthermore, candidates must understand and be able to apply ethical AI principles.
- The recommended knowledge include a basic understanding of Microsoft Azure, AI services, and Windows 10 devices.
- The ideal candidates for the Azure AI engineer jobs include data engineers, Azure developers, and individuals working as AI engineers.
Objectives of the certification exam
The goal of the exam for the AI-100 certification exam also serves as a starting point to becoming a Microsoft Certified Azure AI Engineer Associate. The exam objectives for AI-100 are as follows.
- Analysis of solution requirements.
- Designing AI solutions.
- Implementation and monitoring of AI solutions.
Here is a comprehensive outline of the different subtopics and weight in each domain of the Azure AI Engineer certification exam:
Analysis of Solution requirements (25 to 30%)
- Recommendations of Cognitive Services APIs for addressing business requirements.
- Mapping security requirements to tools, technologies, and processes.
- Selection of software, services, and storage according to a solution.
Designing AI solutions (40 to 45%)
- Designing solutions with one or more pipelines.
- Designing solutions with Cognitive Services.
- Designing solutions implementing Bot framework.
- Designing compute infrastructure for supporting a solution.
- Designing for data governance, integrity, security and compliance objectives.
Implementing and monitoring AI solutions (25 to 30%)
- Implementation of an AI workflow.
- Integration of AI services with solution components.
- Monitoring and evaluation of AI environment.
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2. Microsoft Learning Path
Microsoft also create a path of learning to understand each topics and provides a variety of learning routes, each of which covers the exam’s contents in modules.
- Preparing for AI engineering
- Provisioning and managing Azure Cognitive Services
- Processing and translating the text with Azure Cognitive Services
- Processing and Translating Speech with Azure Cognitive Speech Services
- Creating a Language Understanding solution
- Creating a QnA solution
- Creating conversational AI solutions
- Creating computer vision solutions with Azure Cognitive Services
- Extracting text from images and documents
- Applying knowledge mining with Azure Cognitive Search
What do an Azure AI engineering professional do?
Just trying to becoming an Azure AI engineer is not enough without knowing what it is that they do. What they do serve as the job description of the roles and responsibilities that candidates have to assume in their jobs. Here is a brief job description for an Azure AI engineering professional.
- Automation of processes through the use of machine learning.
- Must understand business problem, setbacks of existing technologies and areas of applications for AI solutions.
- Automation of infrastructure used by the Data Science team.
- Identification and selection of right AI or cognitive computing technologies for addressing problems and creating AI frameworks for application development.
- Testing and deployment of models.
- Development of essential machine learning models and prototype applications by implementing fabricated AI frameworks.
- Verifying the alignment of problem and solutions.
- Participation in the development of AI platforms and transition of projects to the AI landscape.
- Coordinating between data scientists and business analysts.
- Conversion of machine learning models into APIs for allowing access by other applications.
- Development of minimum viable products based on machine learning.
- Utilizing AI for empowering company with new capabilities.
- Research on improvements in machine-learning algorithms.
- Using machine learning for a collection of data inputs in a software development lifecycle.
- Data mining, pattern matching, and pattern recognition.
- Training software based on machine learning for domain-specific tasks.
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Wrapping Up On Azure AI Engineer Salary In 2023
Azure AI Engineer salary will keep rising as industries like tech, financial services, and medical research turn to artificial intelligence.
Azure AI engineers build, manage, and deploy AI solutions that leverage Azure Cognitive Services and Azure Applied AI services.
Equipped with the skills and knowledge to help organizations utilize cutting-edge tech within the field of artificial intelligence and machine learning, Azure AI Engineers will be among the most sought-after tech professionals in the coming years.