Paralegal (General) for Legal Data Annotation
You will help prepare legal materials for AI training by reviewing documents, analyzing case information, and turning legal content into accurate, structured data. The work requires careful judgment about legal terms, procedures, and document context.
- Field
- Law
- Where
- United States, Algeria, Argentina, Austria, Bahrain, Bangladesh +46 more
- Commitment
- part time
- Posted
- yesterday
Pay data for your profession: Lawyer AI trainer jobs
How this pay compares
The title points to labeling and annotation: tagging what's in images, video, audio or documents. What each kind of AI training work pays
At $60/hr (the midpoint of $50 to $70), this role pays more than 7% of the 157 open law roles with a listed pay range, below the median of $115.
Among platforms with 10 or more priced law roles, micro1 has the highest median ($135/hr across 54 roles) and Mercor the lowest ($110/hr across 15).
OpenTrain AI roles that closed since late October stayed listed a median of 31 days (122 roles). OpenTrain AI posted this one yesterday.
Computed from 2,746 open roles we track across Mercor, micro1, Handshake AI, Alignerr, Appen and OpenTrain AI, refreshed daily. Midpoints of listed ranges; “up to” ceilings are left out of medians.
What you would earn at this rate
Per week, before tax
$900
Per month, if the work is steady
$3,900
- Tax
- Contract pay arrives with no tax withheld. A US contractor at this rate and these hours would set aside about $986 a month for self-employment tax plus federal income tax at the 12% bracket (25%, before state tax). Outside the US, your own country's rules apply.
Assumes paid hours only; unpaid assessments, onboarding and gaps between projects lower the real figure. Full take-home calculator · Track what you actually earn
Open law roles on each platform
The same kind of work, priced on every platform we track, with the best-paid open role on each.
| Platform | Open | Median | Best-paid open role |
|---|---|---|---|
| micro1 | 54 | $135/hr | Domain Researcher, Legal$400k-800k/yr |
| OpenTrain AIthis role | 79 | $120/hr | Civil Rights Attorney for Legal AI Evaluation$140-400/hr |
| Mercor | 15 | $110/hr | US Patent Attorney — Prosecution & Litigation$180/hr |
| Alignerr | 9 | $43/hr | Legal Expert: AI Legal Reasoning Review$75-95/hr |
| Handshake AI | 3 | up to $110/hr3 priced | Legal ProfessionalsUp to $150/hr |
“Up to” rows list only ceilings, so their median is a maximum, not comparable with the range midpoints above them.
All 160 open law roles →The full listing
As posted on OpenTrain AI. See the original
The work
You will help prepare legal materials for AI training by reviewing documents, analyzing case information, and turning legal content into accurate, structured data. The work requires careful judgment about legal terms, procedures, and document context.
You will work with legal documents and data quality checks while coordinating remotely with project coordinators on deliverables and project standards.
- Research and analyze legal topics and case materials.
- Review and annotate legal documents, case files, pleadings, and filings.
- Summarize legal content and prepare structured datasets for machine learning projects.
- Use Relativity and other eDiscovery tools to find, categorize, and extract relevant information.
- Check legal data and annotations for accuracy, completeness, and quality.
- Explain legal terminology, procedures, and document context.
- Coordinate remotely with project coordinators on deliverables and milestones.
What it pays and takes
This is a remote, part-time contractor role. Prior AI or data annotation experience is helpful but not required.
- Pay: $50 to $70 per hour.
- Work arrangement: Remote contractor work.
- Location: Open to candidates in the countries listed for this role.
- Language: Fluent English is required.
- Experience: Substantial paralegal experience in a US-based law firm or legal service provider.
- Skills: Legal research, document review, and drafting pleadings and filings.
- Tools: Hands-on familiarity with eDiscovery platforms, especially Relativity.
- Strengths: Clear written and verbal communication, organization, attention to detail, reliability, and care with sensitive legal information.
- Relevant backgrounds may include litigation, corporate, intellectual property, employment, real estate, or other legal practice areas.
How it works
You apply here in about two minutes and finish on the hiring platform. The next step is a short AI interview (technical roles include a coding challenge). Passing it is how you qualify for paid tasks, so take it soon after you are invited.
The hiring platform's application for this job asks for your resume, your LinkedIn profile, your phone number, your location and answers to 5 screening questions.
About AI training work
AI training work uses human-reviewed examples to help artificial intelligence understand language, documents, and real-world tasks. Legal experience is valuable because accurate annotation depends on understanding specialized terminology, procedures, and context; OpenTrain helps people find these roles and apply through its platform.
From applying to your first payment on OpenTrain AI
- 1
Create a profile
Create a free OpenTrain profile with your domains, languages and hourly rate.
- 2
Apply
Apply to the listing. Some listings hire through OpenTrain; others send you to the hiring platform.
- 3
Funded milestones
The client funds each milestone before work starts.
- 4
First payment
OpenTrain pays out to your connected payout method when the client approves the milestone. It doesn't publish a fixed payout schedule.
Sources: OpenTrain: AI training careers, OpenTrain docs: invoicing and payouts
Full OpenTrain AI profile: watch-outs and the public record →Pay history
OpenTrain AI has listed this role at $50-70/hr since Nov 10, 2026 with no change.
Across OpenTrain AI's law roles, the median listed pay was $120/hr on Nov 1, 2026 (60 roles) and is $120/hr as of Nov 11, 2026 (79 roles).
What workers report about OpenTrain AI
Anonymous reports from people who applied or worked there: whether they got work, what they were paid and how fast.
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