ZipRecruiter

Log In

2

Part Time Ai Data Trainer Jobs (NOW HIRING)

micro1 AI

AI Data Trainer - MS Suite - Remote

Denver, CO · Remote

$35 - $50/hr

... proposals, or data-driven reporting, tailored to your industry background. * Document findings and provide actionable feedback to inform the ongoing development of AI systems for business ...

micro1 AI

AI Data Trainer - MS Suite - Remote

Austin, TX · Remote

$35 - $50/hr

... proposals, or data-driven reporting, tailored to your industry background. * Document findings and provide actionable feedback to inform the ongoing development of AI systems for business ...

next page

Showing results 1-20

All JobsAi Data Trainer JobsPart Time Ai Data Trainer Jobs

Part Time Ai Data Trainer information

See salary details

$13

$31

$63

How much do part time ai data trainer jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for part time ai data trainer in the United States is $31.24, according to ZipRecruiter salary data. Most workers in this role earn between $19.95 and $35.58 per hour, depending on experience, location, and employer.

How do I become a part time AI data trainer?

To become a part-time AI data trainer, you typically need strong attention to detail, good communication skills, and familiarity with data annotation tools. Relevant experience in data labeling, machine learning, or related fields can be beneficial, and some roles may require basic knowledge of programming or AI concepts. Many positions are flexible and can be done remotely, often requiring a few hours per day or week.

How much do part time AI data trainers make?

Part-time AI data trainers typically earn between $12 and $20 per hour, depending on experience, location, and the complexity of the tasks. Compensation may also include bonuses or incentives for high-quality data annotation and training performance.

Is there a demand for part time AI Data Trainers?

There is a growing demand for part-time AI Data Trainers as companies seek to improve machine learning models through data annotation and labeling. These roles often require attention to detail, familiarity with AI tools, and flexible schedules, making them suitable for individuals seeking part-time work in the AI industry.

What are some common challenges faced by part time AI data trainers, and how can they be managed?

Part-time AI Data Trainers often encounter challenges such as balancing multiple projects or adapting quickly to changing data labeling guidelines. Additionally, maintaining consistency and quality in annotations while working limited hours can be demanding. To manage these challenges, it’s helpful to establish a structured routine, seek clarification from team leads when guidelines change, and utilize collaborative tools for feedback. Effective communication with peers and supervisors ensures alignment and helps maintain high data quality, which is critical to AI model performance.

What is the difference between Part Time Ai Data Trainer vs Data Annotator?

AspectPart Time Ai Data TrainerData Annotator
Required CredentialsBasic technical skills, training in AI conceptsMinimal; often on-the-job training
Work EnvironmentRemote or office-based, collaborativeRemote or on-site, task-focused
Employer & Industry UsageTech companies, AI startups, research firmsTech companies, data services, AI development

Part Time Ai Data Trainers typically have some technical background and focus on training AI models by providing labeled data and feedback. Data Annotators mainly perform data labeling tasks with minimal training. While both roles support AI development, trainers often require more technical knowledge and engage in training processes, whereas annotators focus on data labeling tasks.

What are the key skills and qualifications needed to thrive as a part time AI data trainer?

To thrive as a Part Time AI Data Trainer, you need strong analytical skills, attention to detail, and familiarity with data labeling, often supported by a background in computer science or related fields. Experience with annotation platforms, data management tools, and sometimes knowledge of programming languages like Python is beneficial. Excellent communication, reliability, and an ability to follow complex guidelines are standout soft skills for this role. These skills ensure high-quality data preparation, which is critical for training accurate and effective AI models.

What is a part time AI data trainer?

Part Time AI Data Trainers are professionals who work on a part-time basis to help train artificial intelligence systems by labeling, annotating, or reviewing data such as text, images, or audio. They play a crucial role in improving the accuracy of AI models by providing high-quality, human-verified data used for machine learning. Their tasks often include evaluating AI-generated outputs, correcting mistakes, and following specific guidelines provided by AI companies or research organizations. This role is popular for people seeking flexible work hours and remote opportunities, as much of the work can be done online.
What cities are hiring for Part Time Ai Data Trainer jobs? Cities with the most Part Time Ai Data Trainer job openings:
What are the most commonly searched types of Ai Data Trainer jobs? The most popular types of Ai Data Trainer jobs are:
What states have the most Part Time Ai Data Trainer jobs? States with the most job openings for Part Time Ai Data Trainer jobs include:
Part Time Ai Data Trainer jobs near you
Infographic showing various Part Time Ai Data Trainer job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, 22% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $64,984 per year, or $31.2 per hour.

AI Data Trainer - MS Suite - Remote

micro1 AI

Denver, CO • Remote

$35 - $50/hr

Part-time

Re-posted 5 days ago

Job description

Role Title: Business Document Expert (Excel, PowerPoint, Word)


Role Type: Contractor


Location: Remote


micro1 is engaging Business Document Experts (Excel, PowerPoint, Word) to participate in a project designed to advance AI capabilities in professional business documentation. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.


Scope of Work


  1. Design and create realistic business tasks and scenarios based on your professional experience involving complex PowerPoint, Excel, and Word deliverables.
  2. Engage in dynamic, prompt-driven conversations with language models, challenging them with work representative of Fortune 500 business environments.
  3. Evaluate AI-generated solutions by comparing multiple model responses, assessing quality, accuracy, and effectiveness for real-world business needs.
  4. Develop and submit detailed assessments highlighting strengths, weaknesses, and areas for model improvement based on your domain expertise.
  5. Contribute cross-functional tasks such as financial modeling, executive presentations, strategic proposals, or data-driven reporting, tailored to your industry background.
  6. Document findings and provide actionable feedback to inform the ongoing development of AI systems for business documentation use cases.
  7. Collaborate asynchronously with project coordinators to ensure the authenticity and utility of submitted challenges and evaluations.


Preferred Qualifications

  1. At least 3 years of hands-on experience in business settings across finance, healthcare, consulting, tech, retail, or related industries.
  2. Extensive proficiency with advanced Excel, PowerPoint, and Word—creating complex models, reports, presentations, and analyses.
  3. Direct experience supporting or driving projects in strategy, operations, sales, marketing, finance, or HR functions within a Fortune 500 context.
  4. Expertise in designing nuanced business scenarios that reflect challenging, high-impact office deliverables.
  5. Strong written and verbal communication skills, with the ability to clearly articulate feedback and rationale in documentation.
  6. Familiarity with conversational interactions or prompt engineering with language models is a plus, but not required.

Apply