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Data Annotation For Ai Jobs in Missouri (NOW HIRING)

micro1 AI

Legal Counsel - AI Trainer

Columbia, MO · Remote

$90 - $130/hr

Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and Qualifications: * Minimum of 3 years of Counsel ...

micro1 AI

Legal Counsel - AI Trainer

Saint Louis, MO · Remote

$90 - $130/hr

Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and Qualifications: * Minimum of 3 years of Counsel ...

micro1 AI

Legal Counsel - AI Trainer

Lees Summit, MO · Remote

$90 - $130/hr

Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and Qualifications: * Minimum of 3 years of Counsel ...

micro1 AI

Legal Counsel - AI Trainer

Springfield, MO · Remote

$90 - $130/hr

Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and Qualifications: * Minimum of 3 years of Counsel ...

APC Integrated Services

AI Engineer

O Fallon, MO · On-site

$110K - $150K/yr

... for AI driven growth, efficiency, and competitive advantage. 4. Data and Model Operations • Develop and oversee data pipelines that support AI solutions, including data preparation, labeling ...

micro1 AI

M&A Attorney - AI Trainer - Remote

Columbia, MO · Remote

$90 - $130/hr

Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and Qualifications: * J.D. from an ABA-accredited ...

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Data Annotation For Ai information

What is data annotation for AI?

Data annotation for AI is the process of labeling or tagging data—such as text, images, audio, or video—to make it understandable for machine learning models. Annotators add relevant information to raw data, helping AI systems learn to recognize patterns and make accurate predictions. This step is crucial for training, validating, and testing AI algorithms, especially in tasks like computer vision and natural language processing. High-quality data annotation directly impacts the effectiveness and reliability of AI applications.

What are some common challenges faced by data annotators working on AI projects, and how can they be addressed?

Data annotators for AI often encounter challenges such as maintaining consistency across large datasets, understanding ambiguous labeling instructions, and managing repetitive tasks. To address these issues, it's important to actively seek clarification on guidelines, participate in team discussions to align on labeling standards, and use annotation tools that flag inconsistencies. Regular feedback sessions with project leads also help improve accuracy and efficiency, fostering a collaborative and supportive work environment.

What are the key skills and qualifications needed to thrive as a data annotation specialist for AI, and why are they important?

To thrive as a Data Annotation Specialist for AI, you need a keen eye for detail, a solid understanding of data labeling concepts, and often a background in the relevant domain (such as language, images, or audio). Proficiency with annotation platforms, data management systems, and basic familiarity with tools like Excel or Python can be highly valuable. Strong communication, consistency, and time management skills help ensure accuracy and meet project deadlines. These abilities are crucial because high-quality, well-annotated data is foundational for training reliable and effective AI models.

What is the difference between Data Annotation For Ai vs Data Labeler?

AspectData Annotation For AiData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, tech companies, AI projectsRemote or on-site, data processing companies
Industry UsageArtificial Intelligence, Machine LearningData management, content moderation
Job FocusPreparing data for AI algorithms through annotationLabeling data for various purposes, including AI

Data Annotation For Ai involves preparing datasets specifically for training AI models, focusing on detailed annotations. Data Labeler is a broader role that includes labeling data for multiple purposes, including AI but also other data management tasks. While both roles require similar skills, Data Annotation For Ai is more specialized towards AI development projects.

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What job categories do people searching Data Annotation For Ai jobs in Missouri look for?

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Data Annotation For Ai jobs near you
Infographic showing various Data Annotation For Ai job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Legal Counsel - AI Trainer

micro1 AI

Columbia, MO • Remote

$90 - $130/hr

Part-time

Re-posted 18 days ago

Job description

Role Title: General Counsel


Role Type: Contractor


Location: Remote


Job Summary: We are seeking seasoned General Counsels for a part-time role at the forefront of legal AI. This opportunity is for elite legal professionals who want to help shape how advanced AI is trained, evaluated, and applied in real-world legal work, especially those who have deep experience with drafting, reviewing, negotiating, and redlining within the tech field.


In this role, you will review, assess, and contribute to contract redlining workflows used to train and evaluate state-of-the-art AI models. Your work will directly improve how these systems identify risk and interpret contract language to create tools with improved precision and legal judgment.



Key Responsibilities:

  1. Perform simulated contract negotiations and redlining exercises.
  2. Create, review, and refine contract negotiation playbooks based on diverse real-world scenarios and company requirements.
  3. Review and assess AI responses to contract scenarios, providing expert feedback to improve model performance and output precision.
  4. Create objective evaluation frameworks and grading criteria to assess AI performance on contract tasks with rigor and consistency.
  5. Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions.


Required Skills and Qualifications:

  1. Minimum of 3 years of Counsel experience focused on technology transactions, particularly negotiating MSAs, NDAs, DPAs, APAs and SPAs.
  2. Exceptional written and verbal communication skills with meticulous attention to detail.
  3. Strong analytical capabilities and ability to translate legal expertise into actionable feedback for AI systems.
  4. Demonstrated commitment to innovation at the intersection of law and technology.
  5. Experience working with cross-disciplinary teams in fast-paced environments.


Preferred Qualifications:

  1. Prior exposure to AI, legal tech, or training initiatives.
  2. Experience at a corporate law firm in either M&A or fund formation for private equity firms.


Why Join:

  1. This is an opportunity to work at the intersection of law and technology.
  2. You will help define how AI is developed for a new generation of legal practitioners.
  3. You will apply your experience in a high-impact research environment.


Compensation Structure:

Compensation is task-based; experts are paid per task that meets the project specifications. The effective hourly rate is based on the average handling time (AHT) of the tasks and may vary by specific task.

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