Data Annotation Specialist Job at Insight Global, Palo Alto, CA

  • Insight Global
  • Palo Alto, CA

Job Description

Job Description

A client of Insight Global is seeking 3 Data Annotation Specialists for an initial 1-month engagement supporting conversational AI tool validation efforts. Resources will manually review and label text-based datasets used to evaluate AI tool selection accuracy. This project will serve as a pilot, with potential for future annotation work as additional datasets become available.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy:

Skills and Requirements

Strong attention to detail

Excellent written communication skills

Ability to follow detailed instructions and documentation

Comfortable performing repetitive, quality-focused work

Strong English language proficiency

Basic Excel proficiency (ability to navigate and work within spreadsheets) Manually annotate and label conversational AI datasets

Evaluate whether the correct tool or response aligns with user intent

Follow annotation guidelines consistently and accurately

Participate in frequent feedback sessions with the HP team

Escalate unclear labeling scenarios for review

Maintain quality and consistency across large volumes of data

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