Job Title: Data Annotation Generalist

Job Type: Contractor

Location: Remote

Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.

Key Responsibilities:

Label, categorize, and annotate diverse datasets with consistency and precision, ensuring adherence to project guidelines and quality standards.
Review, validate, and correct data annotations to maintain the highest levels of data integrity.
Collaborate closely with the customer's team to clarify requirements and resolve ambiguities in data labeling tasks.
Document annotation processes and maintain clear records to support project transparency.
Provide feedback to optimize annotation tools, workflows, and guidelines as projects evolve.
Communicate effectively through written and verbal channels to share insights, raise issues, and recommend improvements.
Adapt to new annotation projects, data types, and evolving instructions as the customer’s needs change.

Required Skills and Qualifications:

Expert-level proficiency in data annotation, labeling, or data preparation for machine learning applications.
Exceptional attention to detail and a commitment to delivering accurate, high-quality work.
Outstanding written and verbal communication skills, with a focus on clarity and collaboration.
Ability to interpret complex instructions and apply them consistently across large datasets.
Comfort working independently in a remote environment, managing time and priorities effectively.
Experience with annotation tools or platforms commonly used in data science or AI development.
Strong analytical skills and a problem-solving mindset.

Preferred Qualifications:

Background in linguistics, computer science, data science, or a related field.
Previous experience contributing to AI training or natural language processing projects.
Familiarity with multiple data modalities, such as text, image, audio, or video annotation.