Overview
Welo Data is looking for detail-oriented and reliable individuals to join our team as Data Labeling Analysts, supporting speech and voice AI systems.
This is a high-impact production role focused on building the datasets that power real-world AI systems. You’ll be working with audio, speech, and language data — helping ensure models are trained on accurate, well-structured, and representative inputs.
While this role is more execution-focused than evaluation-heavy roles, it still requires strong judgment, attention to detail, and consistency. The work sits at the intersection of language, data, and AI systems — where precision and discipline matter at scale.
We’re looking for people who are dependable, focused, and take pride in producing high-quality work, even across repetitive workflows.
Project Details
• Job Title: Project Perseus | Speech & Voice AI Analyst - Polish Speakers
• Hiring in: Onsite (Bay Area, Seattle, NYC, or client-dependent)
• Hours: Full-time, 40 hours per week
• Employment Type: W2 Full-Time Employee
• Work Authorization: Must be authorized to work in the U.S. (no visa sponsorship)
• Pay Rate: $28/hour
Important: This is a 100% onsite position — remote work is not available for this role. To be considered, candidates must be located in or able to commute to one of the following cities: NYC, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, Burlingame, Los Angeles, Washington DC, Boston. Please only apply if you meet this location requirement.
What You’ll Do
• Evaluate AI model outputs and provide structured, high-quality feedback
• Perform audit-based reviews of data and model behavior — identifying patterns, edge cases, and failure modes
• Apply guidelines thoughtfully — and flag when they don’t reflect real-world scenarios
• Contribute to improving evaluation frameworks, not just executing them
• Identify trends in model performance and communicate insights clearly
• Participate in team discussions, calibrations, and stakeholder syncs
• Partner with leads and cross-functional teams to refine quality standards
• Document findings in a clear, concise, and actionable way
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