Data Annotation Specialist, Safety

CanadaRemote

Responsibilities

- Create prompts and safety test cases: Write realistic prompts, user scenarios, and adversarial examples that help evaluate model behavior across safety categories and uncover unsafe, evasive, over-refusing, or policy-inconsistent responses.
- Support quality and calibration: Identify annotation inconsistencies or unclear guidelines, and provide actionable feedback on recurring edge cases, model failures, and opportunities to improve data quality.

We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents.
We believe that our work is instrumental to the widespread adoption of AI.
Cohere is looking for Data Annotation Specialists with backgrounds and skills in Trust & Safety, Content Moderation, AI model evaluation, or related fields.
experience applying nuanced guidelines to complex or ambiguous content.
Successful candidates will be highly detail-oriented, comfortable evaluating safety risks across different user intents and scenarios, and able to make consistent, well-reasoned decisions with a high degree of independence after onboarding.
experience in Content Moderation,Trust and Safety, AI data annotation, LLM evaluation, or a related analytical role, with exposure to quality assurance, red teaming, and/or prompt engineering preferred. -
Experience applying detailed guidelines to complex and sensitive content, with strong contextual and sociocultural judgment and the ability to recognize and manage personal bias.
- Excellent command of written English and the ability to clearly justify content evaluations, including why an output is safe, unsafe, high-quality or low-quality.
Virtual Annotation Test - This assignment will test your written skill through various language-based tasks, such as a a writing sample, interacting with a chat bot, and more.