Disputes Lawyer - AI Trainer
- Status
- Open
- Remote policy
- Remote
- Employment type
- Not stated
- Salary
- Not stated
- Categories
- Litigation-Lawyer, Dispute-Lawyer, German-Law, AI-Trainer, Legal-Consultant, Legal-AI-Trainer, AI-Legal-Trainer, Legal-AI-Training-Specialist, Legal-AI-Training, AI-Trainer-(Legal), Freelance-Legal-Document-AI-Trainer, AI-Legal-Specialist, Legal-AI-Specialist, AI-Legal-Counsel
- Source
- himalayas
- First observed
- 2026-08-20 05:15 UTC
- Last seen
- 2026-08-20 05:15 UTC
- Source claims posted
- 2026-08-20 05:01 UTC
- Consecutive misses
- 4 of 10
What the posting says
About the job
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.
Position: Litigation Lawyer (Germany)
Type:Contract
Compensation:$140–$150/hour
Location:Remote
Commitment:~10 hours/week
Role Responsibilities
Run the same set of prompts across two AI (LLM) platforms.
Compare outputs from both platforms side by side.
Score each response against a standardized rubric we provide.
Submit concise written feedback for every evaluation.
Work independently and adhere to deadlines while maintaining confidentiality under NDA.
Qualifications
Must-Have
Primarily law-firm experience — at least 2 years (3+ preferred) in litigation, disputes, or contentious practice.
Qualified to practise in Germany (Rechtsanwalt/Rechtsanwältin) with strong command of German litigation and procedural law.
Native or fluent German, with precise written communication.
Able to work independently to a rubric and to deadlines.
Resources & Support
For details about the interview process and platform information, please check:
For any help or support, reach out to:
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
#hiringmercor
Originally posted on Himalayas
Quality
- x Salary range stated weight 35%
- + Remote policy stated weight 20%
- + Location stated weight 15%
- + Organisation stated weight 15%
- + Publication date stated weight 15%
Based on 5 observation(s).
- + Days open - fineOpen for 0 days so far
- + Reopen count - fineNever reopened
- + Salary range removed after publication - fineSalary range has not been removed since publication
- + Salary range narrowed - fineSalary range has not narrowed since publication
- + Missing/reappear cycles - fineNo missing-then-reappeared cycles observed
Timeline
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#202198 2026-08-20 05:15 UTCPublished
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#204397 2026-08-20 07:16 UTCNot seenMiss 1 in a row
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#205460 2026-08-20 07:34 UTCNot seenMiss 2 in a row
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#207279 2026-08-20 09:21 UTCNot seenMiss 3 in a row
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#208964 2026-08-20 11:22 UTCNot seenMiss 4 in a row