UK English Data Labeling Analyst – Speech AI (Onsite)

Welo Data; Washington (District of Columbia); On-site; USD 79,901,000 - 82,656,000; Full time

Benefits offered by this job

Paid time off

Paid holidays

Health insurance

Health Savings Account

401(k)

Employee assistance program

Commuter benefits

Onsite meals

Job summary

Welo Data seeks detail-oriented Data Labeling Analysts to support speech and voice AI systems. This 100% onsite role requires commuting to listed US cities and a 40-hour work week.

The position demands native-level English (UK) proficiency, strong written communication, and either 1 year of data labeling experience or a related degree. You will evaluate model outputs and document findings for continuous quality improvement.

Qualifications

• 1 year of work experience in data labeling, annotation, or related content work.
• Or a Bachelor's degree or equivalent in a related field.
• Native-level fluency in English (UK) required.

Responsibilities

• Evaluate AI model outputs and provide structured feedback.
• Perform audit-based reviews of data and model behavior to identify patterns and edge cases.
• Apply guidelines thoughtfully and flag when they do not reflect real-world scenarios.
• Contribute to improving evaluation frameworks beyond execution.
• Identify trends in model performance and communicate insights clearly.
• Participate in team discussions, calibrations, and stakeholder syncs.
• Partner with leads to refine quality standards and document findings clearly.

Skills

English (UK) proficiency

Written communication

Attention to detail

Time management

Ask questions

Education

Bachelor's degree or equivalent

Job description

Welo Data seeks detail-oriented Data Labeling Analysts to support speech and voice AI systems. This 100% onsite role requires commuting to listed US cities and a 40-hour work week.

The position demands native-level English (UK) proficiency, strong written communication, and either 1 year of data labeling experience or a related degree. You will evaluate model outputs and document findings for continuous quality improvement.