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Ai Task Reviewer Jobs in Indiana (NOW HIRING)

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

... tasks with rigor and consistency. * Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions. Required Skills and ...

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Ai Task Reviewer information

What is the difference between Ai Task Reviewer vs Data Annotator?

AspectAi Task ReviewerData Annotator
Required CredentialsBasic computer skills, training in review guidelinesBasic computer skills, training in annotation tools
Work EnvironmentRemote or office-based, reviewing AI outputsRemote or office-based, labeling and annotating data
Industry UsageAI development, machine learning projectsData preparation, machine learning datasets
Search & Comparison IntentUnderstanding review roles in AI projectsUnderstanding data labeling roles in AI

The main difference between an Ai Task Reviewer and a Data Annotator lies in their roles within AI development. Ai Task Reviewers focus on evaluating and validating AI outputs, ensuring quality and accuracy, while Data Annotators are responsible for labeling and preparing data used to train AI models. Both roles are essential in the AI industry, often requiring similar skills but serving different functions in the data pipeline.

Are remote AI task reviewer jobs legit?

Remote AI task reviewer jobs are legitimate positions where individuals evaluate and annotate data to improve AI systems. These roles often require attention to detail, basic computer skills, and sometimes specific training or guidelines, and they are commonly offered by reputable companies in the tech industry.

How to become an AI Task Reviewer?

To become an AI Task Reviewer, candidates typically need strong attention to detail, good understanding of AI and machine learning concepts, and experience with data annotation or content moderation. Relevant skills include familiarity with review platforms, basic knowledge of data labeling tools, and the ability to follow guidelines accurately. Some positions may require a high school diploma or equivalent, with advanced roles favoring prior experience in AI-related tasks.

What are popular job titles related to Ai Task Reviewer jobs in Indiana?

For Ai Task Reviewer jobs in Indiana, the most frequently searched job titles are:

What job categories do people searching Ai Task Reviewer jobs in Indiana look for?

The top searched job categories for Ai Task Reviewer jobs in Indiana are:

What cities in Indiana are hiring for Ai Task Reviewer jobs?

Cities in Indiana with the most Ai Task Reviewer job openings:

Infographic showing various Ai Task Reviewer job openings in Indiana as of August 2026, with employment types broken down into 100% Part Time. Highlights an 100% In-person job distribution.

Legal Counsel - AI Trainer

micro1 AI

Evansville, IN • Remote

$90 - $130/hr

Part-time

Re-posted 17 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.