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Data Annotation Ai Trainer Jobs in Minnesota (NOW HIRING)

Document experimental findings and processes with a focus on clarity for AI training data ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Imaging Tech II - Non-Exempt

MN ยท On-site +1

$38 - $43/hr

Data Annotation * ECG Nice to Have: * IBHRE certification HM's Top Needs: * CCI CRAT or CCT ... for AI development purposes. * Deliver annotation projects assigned and work with other ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. * Experience working with private equity ...

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Data Annotation Ai Trainer information

How much do data annotation AI trainers make?

Data annotation AI trainers typically earn between $15 and $30 per hour, depending on experience, location, and the complexity of the annotation tasks. Entry-level positions may pay closer to minimum wage, while experienced trainers with specialized skills can earn higher wages, especially when working on large datasets or with advanced annotation tools.

What is a data annotation AI trainer?

A Data Annotation AI Trainer is responsible for labeling and annotating data to help train machine learning models. This involves identifying objects, tagging text, or categorizing images to improve AI accuracy. The role requires attention to detail and an understanding of guidelines to ensure high-quality labeled data. AI trainers work closely with data scientists and engineers to refine model performance through precise annotations.

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

To thrive as a Data Annotation Ai Trainer, you need a keen attention to detail, basic data analysis skills, and familiarity with machine learning concepts, often supported by a relevant degree or coursework. Experience with annotation tools like Labelbox, Supervisely, or similar platforms, along with knowledge of data privacy standards, is commonly required. Strong communication, problem-solving ability, and patience help you work effectively in teams and ensure data quality. These skills are essential because they directly influence the accuracy and effectiveness of AI models trained using annotated data.

What does a data annotation AI trainer do?

As a Data Annotation Ai Trainer, your typical day involves reviewing and labeling large datasets, providing feedback to annotation teams, and ensuring that data quality meets project standards. You'll often collaborate with data scientists, machine learning engineers, and project managers to clarify guidelines and resolve ambiguities. Periodically, you may help develop or refine documentation and training materials to improve annotation consistency. The role requires both independent work and open communication to maintain high accuracy and support AI development initiatives.

Is data annotation AI trainer job legitimate?

Data annotation AI trainer jobs are legitimate roles involving labeling data to help train machine learning models. These positions often require attention to detail and familiarity with annotation tools, and they are commonly offered by technology companies and AI service providers. However, job seekers should verify the employer's credibility to avoid scams.
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Infographic showing various Data Annotation Ai Trainer job openings in Minnesota as of July 2026, with employment types broken down into 74% Full Time, 23% Part Time, and 3% Contract. Highlights an 71% Physical, 3% Hybrid, and 26% Remote job distribution.

AI Trainer - Microbiology Expert

micro1 AI

Minneapolis, MN โ€ข Remote

$70 - $90/hr

Part-time

Posted 8 days ago


Job description

Role Title: Microbiologist


Role Type: Contractor


Location: Remote


micro1 is engaging Microbiologists to contribute their scientific expertise to a unique customer project. 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 โ€” your domain knowledge is what matters.


Key Responsibilities:

  1. Investigate and analyze the development, morphology, and behavior of microscopic organisms including bacteria, fungi, and algae.
  2. Contribute to the study of the relationship between microorganisms and disease, supporting projects involving medical microbiology.
  3. Assess the impact of antibiotics and other agents on microbial populations, providing insights for AI model accuracy.
  4. Document experimental findings and processes with a focus on clarity for AI training data.
  5. Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.
  6. Provide written and verbal expertise on microbiological phenomena and their relevance to real-world and computational contexts.
  7. Utilize rubrics and established evaluation criteria to assess data quality and support AI training workflows.


Required Skills and Qualifications:

  1. Bachelorโ€™s degree or higher in Biology, Microbiology, Chemistry, or a related field.
  2. Extensive knowledge of bacterial, fungal, and algal systems.
  3. Demonstrated expertise in investigating microbial structure and physiology.
  4. Strong written and verbal communication skills for technical and interdisciplinary collaboration.
  5. Ability to document processes and findings clearly for integration into AI systems.
  6. Comfort working independently in a fully remote, digital-first environment.
  7. Attention to detail and commitment to scientific accuracy.


Preferred Qualifications:

  1. Prior experience developing or applying rubrics in scientific or educational contexts.
  2. Experience with AI, machine learning, or annotation projects related to biology or microbiology.
  3. Advanced degree (Masterโ€™s or PhD) in a relevant field.