Danish Speech Data Labeling Specialist (Onsite)

Welo Global; Burlingame (CA); On-site; USD 36,000 - 39,000; Full time

Benefits offered by this job

Paid Vacation: 6 days

Paid Holidays: 2 days

Paid Sick Leave: accrued per state law

Medical, Dental, Vision Insurance

Health Savings Account (HSA)

401(k) Retirement Plan

Employee Assistance Program

Voluntary benefits

Job summary

Welocalize in the United States is seeking a Data Labeling Analyst to support speech and language AI projects. This onsite role emphasizes high-volume labeling, strict guidelines, and data integrity across audio datasets.

Candidates should be dependable, detail-oriented, and capable of maintaining throughput in a structured environment. Responsibilities include transcription, tagging, and annotation for training data, with compensation $26–$28 per hour and full-time, W2 employment.

Qualifications

• Native-level fluency in Danish.
• Strong written communication skills and language fundamentals.
• 1 year of work experience in data labeling, annotation, or content-focused work; or a Bachelor’s degree or equivalent academic qualification in a related field.

Responsibilities

• Execute high-volume data labeling and annotation tasks across speech and voice datasets
• Follow detailed guidelines to ensure consistency, accuracy, and data integrity at scale
• Work with audio and language data, including transcription, categorization, and tagging
• Maintain strong throughput while meeting quality expectations
• Escalate unclear or ambiguous cases appropriately
• Adapt to evolving guidelines and workflows as systems and requirements change
• Support baseline data production needs for AI training pipelines
• Contribute to team calibrations and quality alignment sessions

Skills

Danish language

Attention to detail

Follow detailed instructions

Time management

Education

Bachelor's degree or equivalent

Job description

Welocalize in the United States is seeking a Data Labeling Analyst to support speech and language AI projects. This onsite role emphasizes high-volume labeling, strict guidelines, and data integrity across audio datasets.

Candidates should be dependable, detail-oriented, and capable of maintaining throughput in a structured environment. Responsibilities include transcription, tagging, and annotation for training data, with compensation $26–$28 per hour and full-time, W2 employment.