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How much do part time google cloud ai jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for part time google cloud ai in the United States is $62.89, according to ZipRecruiter salary data. Most workers in this role earn between $53.61 and $71.63 per hour, depending on experience, location, and employer.

What is the difference between Part Time Google Cloud Ai vs Part Time Data Analyst?

AspectPart Time Google Cloud AiPart Time Data Analyst
Required CredentialsGoogle Cloud certifications, AI/ML knowledgeData analysis certifications, SQL, Excel skills
Work EnvironmentCloud platforms, remote or hybridOffice or remote, data-focused environment
Industry UsageTech, AI, cloud servicesBusiness, finance, marketing
Search & Comparison IntentUnderstanding AI roles in cloud computingAnalyzing data for insights

Part Time Google Cloud Ai roles focus on developing and deploying AI solutions on cloud platforms, requiring cloud certifications and AI expertise. In contrast, Part Time Data Analyst positions involve interpreting data to inform business decisions, emphasizing data analysis skills. Both roles are often remote and serve different industry needs, but they share a focus on data and technology.

What are the key skills and qualifications needed to thrive as a Part Time Google Cloud AI professional, and why are they important?

To excel as a Part Time Google Cloud AI professional, you typically need a strong background in computer science, machine learning principles, and experience with cloud platforms, often supported by relevant coursework or certifications. Familiarity with Google Cloud tools like AI Platform, TensorFlow, BigQuery, and APIs, as well as Google Cloud Professional certifications, is highly valued. Strong problem-solving abilities, effective communication, and adaptability help you collaborate on projects and address evolving client or business needs. These skills and qualities ensure you can develop, deploy, and maintain AI solutions efficiently while meeting organizational goals.

How does a part-time Google Cloud AI specialist typically collaborate with cross-functional teams and stakeholders?

As a part-time Google Cloud AI specialist, you will frequently work alongside data scientists, software engineers, and business stakeholders to implement AI solutions using Google Cloud technologies. Collaboration often involves participating in sprint meetings, clarifying project requirements, and integrating AI models into existing workflows. Since the role is part-time, strong communication and documentation skills are essential to ensure seamless handoffs and project continuity. You'll also leverage tools like Google Meet and shared project boards to stay aligned with team objectives and timelines.

What is a Part Time Google Cloud AI job?

A Part Time Google Cloud AI job typically involves working with Google's cloud-based artificial intelligence tools and services, such as machine learning models, data analytics, and AI-driven applications. These roles can include tasks like developing, deploying, or maintaining AI solutions on Google Cloud Platform (GCP), often in a support, engineering, or data science capacity. Part-time positions may offer flexible hours and are ideal for students, freelancers, or professionals seeking to expand their expertise in cloud-based AI technologies while managing other commitments.
More about Part Time Google Cloud Ai jobs
What are the most commonly searched types of Google Cloud Ai jobs? The most popular types of Google Cloud Ai jobs are:
What states have the most Part Time Google Cloud Ai jobs? States with the most job openings for Part Time Google Cloud Ai jobs include:
What job categories do people searching Part Time Google Cloud Ai jobs look for? The top searched job categories for Part Time Google Cloud Ai jobs are:
Part Time Google Cloud Ai jobs near you
Infographic showing various Part Time Google Cloud Ai job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $130,802 per year, or $62.9 per hour.

Adjunct Faculty - AI and Cloud Computing

Harper College

Palatine, IL • On-site

Part-time

Re-posted 12 hours ago

Harper College rating

9.2

Company rating: 9.2 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

15th of 613 rated colleges and universities

Job description


Courses to be taught:
AIC 110 - Introduction to Artificial Intelligence
Other courses in AI and Cloud Computing as needed
Responsibilities
Job Description:
Deliver course content that aligns with the college's curriculum standards and student learning outcomes.
Develop course syllabi, assignments, and assessments that reflect current industry practices and ensure course outcomes are met.
Foster an inclusive and engaging learning environment that accommodates diverse learning styles and promotes student success.
Use technology and other resources to enhance course delivery and student engagement, including online, hybrid, or face-to-face modalities.
Maintain accurate records of student's progress and grades.
Must adhere to mid-term verification and final grade posting deadlines.
Adhere to institutional policies and procedures, including those related to academic integrity and accessibility.
Ability to teach topics such as artificial intelligence concepts, cloud computing platforms, machine learning fundamentals, and AI applications.
Experience with industry tools and platforms such as AWS, Microsoft Azure, Google Cloud, Python, or similar technologies.
Commitment to continuous learning to stay current with emerging AI and cloud technologies.
Qualifications
Experience Requirements:
A minimum of one year of full-time, non-teaching professional experience (2,000 hrs) in artificial intelligence, cloud computing, software engineering, data science, or a related field.
Significant professional experience applying AI or cloud technologies in real-world environments.
Preferred Experience:
Prior teaching or training experience in higher education, corporate training, or workforce development.
Education Requirements:
Bachelor's degree in computer science, information technology, or a closely related field.
Preferred Education Requirements:
Industry-recognized certifications (e.g., AWS Certified Solutions Architect, Microsoft Azure certifications, Google Cloud certifications, or similar).

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