Data Annotation Specialist - German Writer/translator

Cohere Cohere · AI Frontier · Canada · Data Quality (Contract)

Cohere is seeking a Data Annotation Specialist with native or near-native German proficiency to label, rank, audit, and correct machine learning data. This part-time, remote, independent contractor role involves improving LLM performance through meticulous data handling and feedback, with a focus on German language tasks. Requires basic data manipulation skills and a high tolerance for repetitive work.

What you'd actually do

  1. Label and Rank: Accurately label and rank machine learning data with advanced proficiency in German, ensuring data integrity and quality.
  2. Audit and Correct: Scrutinize and rectify any inaccuracies in language data (may include text, image, JSON, TSV/CSV, Markdown), maintaining the highest standard of data accuracy.
  3. Reading and Text-Based Tasks: Efficiently complete reading and text-based assignments, with high attention to detail.
  4. Preference-Based Tasks: Evaluate and complete tasks, assessing which responses in German best conform to project guidelines.
  5. Recommend Optimizations: Identify and suggest opportunities for improving data quality and model performance in German language tasks.

Skills

Required

  • Native or near-native proficiency in German
  • Excellent command over English
  • Expert reading and writing skills
  • Basic familiarity with JSON/TSV/CSV/Markdown data manipulation
  • Strong attention to detail and commitment to accuracy
  • High tolerance for repetitive and monotonous work
  • Ability to follow complex instructions, navigate ambiguity and work independently
  • Superb sense of urgency and time management
  • Reliable laptop

Nice to have

  • Curiosity about technology and a knack for tackling problems in creative ways.

What the JD emphasized

  • exceptional Modern Standard German Writing, Translation, and Data Manipulation skill
  • Native or near-native proficiency in German
  • Expert reading and writing skills - which you are ready to prove on our written test.

Other signals

  • Data quality is foundational to this process.
  • By labelling, ranking, auditing, and correcting text output, you will improve Large Language Model’s performance for iterations to come