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Healthcare AI QA Labeler – Central American Spanish Speaker

Alignerr · Remote · Voice / audio

Healthcare AI QA Labeler – Central American Spanish Speaker is an open role at Alignerr, available remotely, with pay listed as $15–$20/hr.

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At a glance

Pay
$15–$20/hrStated by Alignerr
Location
Remote
Work type
Voice / audio
Listed
Since Oct 11, last confirmed Oct 24

How the pay compares

This role$20
Alignerr median$75
Healthcare roles median$90
All roles median$60

Higher than 0% of the 88 distinct hourly rates advertised for Healthcare roles right now. Hourly USD, top of each advertised range, one count per distinct rate. Same method as the Pay Index.

From Alignerr’s listing

“Healthcare AI QA Labeler – Central American Spanish Speaker About the Role What if your deep fluency in Central American Spanish could directly shape how AI assistants interact with patients across the healthcare system?”
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Healthcare AI QA Labeler – Central American Spanish Speaker About the Role What if your deep fluency in Central American Spanish could directly shape how AI assistants interact with patients across the healthcare system? We're looking for detail-oriented QA labelers — particularly those with roots in Honduras, Guatemala, or El Salvador — to evaluate and annotate AI healthcare call transcripts in Central American Spanish. Los Angeles is home to one of the largest and most vibrant Central American communities in the United States, and that linguistic and cultural insight is exactly what this project demands. You'll assess the nuanced reality of healthcare communication: identifying where the AI handles patient concerns appropriately, how it manages unclear audio conditions, whether it confirms key patient details correctly, and whether its responses align with real care protocols. This is a fully remote, flexible contract role. No prior AI experience needed — just native or near-native Central American Spanish fluency and a commitment to careful, consistent evaluation work. Organization : Labelbox Type : Hourly Contract Location : Remote Commitment : Flexible hours What You'll Do Review transcripts of AI-assisted healthcare calls and evaluate interaction quality Assess how the AI handles patient responses, including unclear or difficult audio conditions such as coughs, mumbles, or whispers Identify whether the AI correctly confirms key patient information (date of birth, appointment details, etc.) Evaluate the AI's ability to address patient health concerns while staying within appropriate boundaries Assess the clarity and completeness of information provided to patients about scheduling and next steps Follow detailed annotation guidelines and labeling conventions consistently across all calls Flag instances where the AI response may be unclear or where patient confusion occurs Maintain high accuracy and consistency across large volumes of call transcripts Work indepe

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Frequently asked questions

How do I apply for the Healthcare AI QA Labeler – Central American Spanish Speaker role at Alignerr?

Applications go through Alignerr's own portal - HumanSourcer links to the listing and never collects applications or handles hiring. Alignerr's access model is "Open / self-serve" (Open roles / applications). This listing was first seen here on October 11, 2026 and was still live at the last check.

Is the Healthcare AI QA Labeler – Central American Spanish Speaker role at Alignerr remote?

Yes - Alignerr lists this role as remote.

What does the Healthcare AI QA Labeler – Central American Spanish Speaker role at Alignerr pay?

Alignerr lists this role's pay as $15–$20/hr, quoted from the listing rather than estimated.

What kind of work is Healthcare AI QA Labeler – Central American Spanish Speaker?

Voice / audio. AI training, evaluation, coding, writing and specialist review

Is Alignerr a legitimate AI-training platform?

Labelbox expert network - and that relationship is rated "Confirmed" here because it can be checked against labelbox.com rather than taken on Alignerr's word. Confidence describes how well the ownership is evidenced. It is not a rating of how the platform treats the people who work for it, which no public source covers reliably.

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