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Data Annotation Ai Training Jobs in Wisconsin (NOW HIRING)

micro1 AI

Legal AI Trainer - Remote

Green Bay, WI · Remote

$90 - $150/hr

Collaborate with product and research teams to refine data, guidelines, and best practices for AI ... Prior exposure to AI, legal tech, or training initiatives. Why Join: * This is an opportunity to ...

micro1 AI

Legal Counsel - AI Trainer

Green Bay, WI · Remote

$90 - $130/hr

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 at a corporate law firm in ...

micro1 AI

Legal Counsel - AI Trainer

Kenosha, WI · Remote

$90 - $130/hr

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 at a corporate law firm in ...

Socket.dev

WI · On-site

... AI training programs for a customer office-based and computer-facing team members. This role helps participants build measurable proficiency in prompt engineering, workflow automation, data ...

New

BlackCube Labs

WI · On-site

AI & Data Solutions Architect (CPG/Retail) Coverage: Multiple U.S. accounts (deep focus on 2-3 ... and training; licensure and certifications; and other business and organizational needs. The ...

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Infographic showing various Data Annotation Ai Training job openings in Wisconsin as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 15% Part Time, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution.

Legal AI Trainer - Remote

Green Bay, WI • Remote

micro1 AI
Software Development • 11 - 50 employees
Learn more about micro1 AIexternal

$90 - $150/hr

Part-time

Posted 25 days ago

Job description

Role Title: Funds Attorney


Role Type: Contractor


Location: Remote


We are seeking seasoned Funds Attorneys for a part-time role at the forefront of legal AI. This opportunity is for elite lawyers 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. Review and assess AI responses to contract scenarios, providing expert feedback to improve model performance and output precision.
  3. Create objective evaluation frameworks and grading criteria to assess AI performance on contract tasks with rigor and consistency.
  4. Collaborate with product and research teams to refine data, guidelines, and best practices for AI-driven contract review solutions.


Required Skills and Qualifications:

  1. J.D. from an ABA-accredited law school.
  2. Active bar admission in at least one U.S. jurisdiction.
  3. Minimum of 2 years in the funds department of a corporate law firm.
  4. Familiarity with standard M&A agreements, including LPA’s, subscription agreements, and side letters.
  5. Exceptional written and verbal communication skills with meticulous attention to detail.
  6. Strong analytical capabilities and ability to translate legal expertise into actionable feedback for AI systems.
  7. Demonstrated commitment to innovation at the intersection of law and technology.
  8. Experience working with cross-disciplinary teams in fast-paced environments.


Preferred Qualifications:

  1. Prior exposure to AI, legal tech, or training initiatives.


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, meaning experts are paid per completed task that meets the project specifications. The average handling time (AHT) is approximately 3.5 hours per task, and the effective hourly rate will depend on the number of tasks completed and successfully signed off.

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