Data Annotator for Large Language Model Fine-Tuning

We are seeking meticulous and detail-oriented Data Annotators to prepare high-quality datasets for fine-tuning large language models (LLMs). As a Data Annotator, you will be responsible for labeling, curating, and verifying data from various sources to ensure accuracy, consistency, and relevancy for machine learning tasks. Your work will directly contribute to enhancing the performance and contextual understanding of cutting-edge LLMs.

Key Responsibilities:
• Annotate and label datasets according to predefined guidelines, including text, images, or multimedia content.
• Review and validate existing annotations to maintain consistency and accuracy.
• Identify and flag ambiguous, incomplete, or incorrect data and provide necessary corrections or feedback.
• Collaborate with the data science team to improve annotation guidelines and processes.
• Ensure timely delivery of annotated datasets to meet project deadlines.
• annotation challenges and propose enhancements to the process.

Requirements:
• Strong attention to detail and ability to follow complex instructions accurately.
• Familiarity with machine learning concepts and LLM fine-tuning is a plus.
• Excellent written communication skills and proficiency in English; knowledge of other languages is a bonus.
• Ability to work independently with minimal supervision in a deadline-driven environment.
• Experience using annotation tools (e.g., Label Studio, Prodigy, or similar platforms) is an advantage.
• Proficiency in identifying sensitive or inappropriate content and handling it responsibly.


Preferred Qualifications:
• Previous experience in data annotation, curation, or preparation for machine learning projects.
• Educational background in linguistics, data science, computer science, or related fields.
• Knowledge of natural language processing (NLP) concepts and applications.

What We Offer:

• Flexible working hours with the ability to work remotely.
• Opportunity to contribute to state-of-the-art AI and LLM development.
• Competitive compensation based on performance and deliverables.
• Professional growth through exposure to innovative AI technologies and projects.

How to Apply:

Please send your CV and a brief cover letter explaining your interest in this role. Shortlisted candidates may be required to complete a small annotation task to assess their skills.