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Cloud Computing Internship Jobs in Michigan (NOW HIRING)

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How much do cloud computing internship jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for cloud computing internship in Michigan is $13.55, according to ZipRecruiter salary data. Most workers in this role earn between $10.91 and $15.29 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed for a cloud computing internship?

To thrive as a Cloud Computing Intern, a solid understanding of computer science fundamentals, familiarity with cloud architectures, and basic programming skills are essential, often demonstrated through coursework or relevant projects. Interns frequently work with platforms like AWS, Azure, or Google Cloud, and may benefit from introductory certifications such as AWS Cloud Practitioner. Strong problem-solving skills, effective communication, and a willingness to learn new technologies help interns stand out in collaborative, fast-paced environments. These abilities enable interns to adapt quickly, contribute meaningfully to technical projects, and develop valuable industry experience.

What is a cloud computing internship?

A Cloud Computing Internship is a temporary position that provides hands-on experience with cloud technologies, platforms, and services. Interns may work on projects involving cloud infrastructure, virtualization, security, automation, and DevOps. They typically use platforms like AWS, Azure, or Google Cloud to develop, test, and deploy applications. This role helps interns build technical skills, gain industry exposure, and prepare for cloud-related careers.

What types of projects or tasks can I expect to work on during a cloud computing internship?

As a Cloud Computing Intern, you can expect to work on tasks such as deploying cloud-based applications, assisting with infrastructure automation, and supporting cloud migration projects. You may also help monitor and optimize cloud resources, write scripts to automate processes, or participate in troubleshooting technical issues with the cloud team. Interns are often given opportunities to collaborate with experienced engineers, gain hands-on experience with leading cloud platforms, and contribute to real-world solutions. This hands-on work helps you develop practical skills and build a strong foundation for a future career in cloud computing.

What are the most commonly searched types of Cloud Computing jobs in Michigan? The most popular types of Cloud Computing jobs in Michigan are:
What are popular job titles related to Cloud Computing Internship jobs in Michigan? For Cloud Computing Internship jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Cloud Computing Internship jobs in Michigan look for? The top searched job categories for Cloud Computing Internship jobs in Michigan are:
What cities in Michigan are hiring for Cloud Computing Internship jobs? Cities in Michigan with the most Cloud Computing Internship job openings:
Cloud Computing Internship jobs near you
Infographic showing various Cloud Computing Internship job openings in Michigan as of August 2026, with employment types broken down into 85% Full Time, 8% Part Time, and 7% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $28,181 per year, or $13.5 per hour.

Software Engineer

FEV North America Inc

Auburn Hills, MI • On-site

Other

Posted 3 days ago

New

Job description

Description

Support the development and deployment of next-generation software solutions in the areas of Generative AI, Physical AI, Cloud Computing, and Embedded Systems. The position will contribute to the design, implementation, testing, and integration of software products while collaborating with multidisciplinary engineering teams. The engineer is expected to continuously develop technical skills and actively participate in innovation initiatives supporting automotive and intelligent mobility applications.

  • Develop software applications and services using modern programming languages and development frameworks. 
  • Support the development and deployment of Generative AI solutions, including AI assistants, intelligent automation tools, and machine learning applications. 
  • Contribute to Physical AI projects involving robotics, autonomous systems, digital twins, simulation environments, and sensor-based applications. 
  • Develop and maintain cloud-native applications and services on platforms such as Microsoft Azure, AWS, or Google Cloud.
  • Support embedded software development activities for automotive and edge-computing systems when required. 
  • Participate in software architecture design, coding, unit testing, debugging, and validation activities. 
  • Collaborate with systems, software, data, and hardware engineers to deliver integrated solutions. 
  • Develop APIs, data processing pipelines, and software tools to support engineering projects. 
  • Participate in code reviews and ensure compliance with software quality standards. 
  • Document software designs, technical solutions, and development activities. 
  • Stay current with emerging technologies in AI, cloud computing, and software engineering. 

Requirements

  • Bachelor's or Master's degree in Computer Engineering, Software Engineering, Computer Science, Electrical Engineering, or a related technical field.  
  • 0-3 years of software development experience. 
  • Academic, internship, capstone project, or personal project experience in software development is acceptable. 
  • Experience in one or more programming languages such as Python, C++, C#, Java, or JavaScript. 
  • Exposure to embedded software development, Linux, RTOS, or automotive software development is considered an advantage.
  • Strong analytical, problem-solving, and communication skills. 
  • Self-motivated with a willingness to learn new technologies and work in fast-paced engineering environments. 
  • Solid understanding of software engineering fundamentals, algorithms, and object-oriented programming. 
  • Knowledge of AI/ML concepts and interest in Generative AI technologies. 
  • Familiarity with cloud platforms (Azure preferred). 
  • Understanding of software development lifecycle and Agile methodologies. 
  • Experience with Git or similar version control tools. 

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