Project Perseus | Speech & Voice AI Analyst - Portuguese (Brazil) Speakers at Welo Global
Sunnyvale, CA
$54,080–$58,240
Jul 15, 2026
Sunnyvale, CA
Jul 21, 2026
What this job asks for AI summary
A full-time, onsite production role focused on annotating and labeling audio, speech, and language datasets used to train AI systems. Day-to-day work involves transcription, categorization, and tagging at high volume while adhering closely to quality guidelines. Suited to detail-oriented candidates with native-level Brazilian Portuguese fluency and some background in data labeling or content work.
Junior level · 1+ years · New York-Newark-Jersey City, NY-NJ-PA · Full-time
Pay in the description: $26–$28/hr
We read this from the posting text with AI. Skim the description below before ruling yourself out.
Why we read it this way (6)
This role is posted across multiple metro areas simultaneously (NYC, Seattle/Bellevue/Redmond, San Francisco/Sunnyvale/Burlingame, Austin, Los Angeles, Washington DC, Chicago, Boston). The CBSA shown (New York) is one of several valid locations; the actual work site is client-dependent.
The SOC classification is uncertain. Data labeling/annotation work sits awkwardly in the SOC taxonomy — 15-2031 (Operations Research Analysts) is the closest available code for data-focused production work, but 15-1299 (Computer Occupations, All Other) is a reasonable alternative. Neither is a perfect fit for a high-volume annotation production role.
The experience requirement is stated as '1 year of work experience in data labeling, annotation, or content-focused work; OR a Bachelor's degree or equivalent.' Because a degree substitutes for experience (and vice versa), neither is a hard gate alone — the degree requirement is set to None accordingly.
Native-level fluency in Portuguese (Brazil) is explicitly listed under 'What We're Looking For' and is treated as a hard requirement.
Familiarity with AI, speech technology, or language data is explicitly called 'a plus' in the posting and is marked as preferred.
Ignored 2 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): speech/audio data annotation, AI/ML data pipelines.
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