UK English Data Labeling Analyst - Speech AI (Onsite)

Welocalize, Inc.

Boston (MA)

On-site

USD 79,901,000 - 88,166,000

Full time

3 days ago
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Benefits offered by this job

Paid vacation
Holiday pay
Sick leave
Medical insurance
401k
Employee assistance

Job summary

Welocalize, Inc. is seeking Data Labeling Analysts for the Welo Data program to support speech and voice AI systems. This is a 100% onsite, full-time role (40 hours per week) requiring work in the U.S.

locations. You will evaluate AI model outputs and provide structured, high-quality feedback to improve datasets. Ideal candidates have native-level English (UK), strong written communication, and either 1 year of labeling experience or a related Bachelor's degree.

Qualifications

  • 1 year of work experience in data labeling, annotation, or content-focused work; or a Bachelor's degree or equivalent in a related field.
  • Strong attention to detail and ability to maintain accuracy in repetitive tasks.
  • Ability to follow detailed instructions and apply guidelines consistently.

Responsibilities

  • Evaluate AI model outputs and provide structured, high-quality feedback
  • Perform audit-based reviews of data and model behavior — identifying patterns and edge cases
  • Apply guidelines thoughtfully and flag when they don’t reflect real-world scenarios
  • Contribute to improving evaluation frameworks
  • Identify trends in model performance and communicate insights clearly
  • Participate in team discussions, calibrations, and stakeholder syncs
  • Document findings in a clear, concise, actionable way

Skills

Native English (UK)
Attention to detail
Written communication
Time management

Education

Bachelor's degree or equivalent

Job description

Welocalize, Inc. is seeking Data Labeling Analysts for the Welo Data program to support speech and voice AI systems. This is a 100% onsite, full-time role (40 hours per week) requiring work in the U.S.

locations. You will evaluate AI model outputs and provide structured, high-quality feedback to improve datasets. Ideal candidates have native-level English (UK), strong written communication, and either 1 year of labeling experience or a related Bachelor's degree.

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