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Welo Data is hiring a Data Labeling Analyst in Washington State to support AI systems by executing data labeling tasks. This full-time position requires professional-level fluency in Hungarian and offers exposure to large-scale AI operations.
The role focuses on ensuring data integrity and involves detailed guidelines to produce high-quality datasets as inputs for AI models. Join a team that values accuracy and consistency in ways that shape modern AI.
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.
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: New York City, Seattle, Bellevue, Redmond, San Francisco, Sunnyvale, or Burlingame. Please only apply if you meet this location requirement.
Onsite Perks (where applicable):
Free breakfast, lunch, and dinner
Stocked micro-kitchens with snacks and beverages
Commuter benefits, including shuttles and bike-to-work options
Unique campus features depending on location
This role is a critical part of how modern AI systems are built. The data you produce directly impacts how speech and voice models understand and interact with real users.
It’s a great entry point into AI operations, offering exposure to large-scale systems and the opportunity to build foundational experience in data, language, and AI workflows.