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Entry Level Ai Data Trainer Jobs in Michigan (NOW HIRING)

Document laboratory methodologies, data, and findings clearly and accurately, ensuring ... training datasets and reasoning capabilities of AI systems. Preferred Qualifications * Advanced ...

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Entry Level Ai Data Trainer information

What does an entry level AI data trainer do?

An Entry Level AI Data Trainer is responsible for preparing, labeling, and organizing data that is used to train artificial intelligence models. This involves tasks such as categorizing images, annotating text, and ensuring that data is accurate and relevant for machine learning algorithms. They work closely with data scientists and engineers to improve the quality of AI systems by providing clean and well-labeled datasets. The role is a great way to start a career in artificial intelligence, as it offers hands-on experience with data and insights into how AI models are developed.

What are the key skills and qualifications needed to thrive as an entry level AI data trainer?

To thrive as an Entry Level AI Data Trainer, you need strong analytical skills, attention to detail, and a foundational understanding of data annotation processes, often supported by a bachelor's degree in a related field. Familiarity with data labeling tools, content management systems, and basic programming or scripting (such as Python) is typically required. Excellent communication, teamwork, and adaptability help you effectively interpret guidelines and collaborate with cross-functional teams. These skills ensure high-quality data preparation, which is essential for developing accurate and reliable AI models.

What types of tasks and collaboration can I expect as an entry level AI data trainer?

As an Entry Level AI Data Trainer, you will primarily be responsible for labeling, annotating, and curating data sets to help improve machine learning models. Your daily tasks often include reviewing text, images, or audio and providing accurate labels according to detailed guidelines. You will frequently collaborate with data scientists, engineers, and other trainers to ensure consistency and quality in the data. This collaborative environment offers valuable exposure to the AI development process, and high performers often have opportunities to advance into more specialized roles over time.

What is the difference between Entry Level Ai Data Trainer vs Data Annotator?

AspectEntry Level Ai Data TrainerData Annotator
Required CredentialsHigh school diploma or equivalent; some roles prefer basic technical skillsHigh school diploma or equivalent; no specialized certifications typically needed
Work EnvironmentOffice or remote; collaborative with AI teamsOffice or remote; focused on labeling data
Employer & Industry UsageTech companies, AI startups, research labsTech companies, data labeling services, AI firms

While both roles involve working with data, Entry Level Ai Data Trainers focus on training AI models by providing structured data and feedback, often requiring some technical understanding. Data Annotators primarily label and categorize data to prepare datasets for AI training. The roles are similar in work environment and industry but differ in responsibilities and skill requirements.

What are the most commonly searched types of Ai Data Trainer jobs in Michigan?

The most popular types of Ai Data Trainer jobs in Michigan are:

What are popular job titles related to Entry Level Ai Data Trainer jobs in Michigan?

For Entry Level Ai Data Trainer jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Entry Level Ai Data Trainer jobs in Michigan look for?

The top searched job categories for Entry Level Ai Data Trainer jobs in Michigan are:

Infographic showing various Entry Level Ai Data Trainer job openings in Michigan as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 13% Part Time, 2% Temporary, 3% Contract, and 1% Nights. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

AI Training Specialist - Chemistry

micro1 AI

Warren, MI • Remote

$70 - $90/hr

Part-time

Posted 21 days ago


Job description

Role Title: Chemistry Specialist


Role Type: Contractor


Location: Remote


micro1 is engaging Chemistry Specialists to participate in a project supporting a leading customer in the scientific and research domain. 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. No prior experience in AI is required — your domain knowledge is what matters.


Scope of Work

  1. Conduct qualitative and quantitative chemical analyses and experiments to support product development, quality control, or process optimization.
  2. Design and interpret complex laboratory experiments involving chemical reactions, synthesis, and separation techniques.
  3. Document laboratory methodologies, data, and findings clearly and accurately, ensuring reproducibility and scientific integrity.
  4. Critically evaluate experimental outcomes to propose improvements or new investigative approaches.
  5. Collaborate and communicate effectively in written and verbal formats with project stakeholders, providing insights and recommendations.
  6. Translate intricate chemistry concepts and experimental results into clear, actionable information for non-specialist audiences.
  7. Contribute domain-specific expertise to enhance the training datasets and reasoning capabilities of AI systems.


Preferred Qualifications

  1. Advanced degree (PhD preferred) in Chemistry or closely related field.
  2. Extensive hands-on experience with wet lab techniques, experimental design, and instrumentation.
  3. Deep understanding of chemical reactions, analytical chemistry, and laboratory best practices.
  4. Demonstrated critical thinking skills and a record of innovative problem-solving in research or applied chemistry settings.
  5. Strong written and verbal communication skills, with the ability to convey technical concepts clearly.
  6. Experience contributing to interdisciplinary projects or cross-functional collaborations.
  7. Familiarity with quality control protocols, safety standards, and regulatory guidelines is a plus.