Responsibilities
- Create and maintain structured data labeling methodologies with detailed, scalable annotation guidelines.
- Define and monitor data quality standards, including inter-annotator consistency metrics.
- Investigate and develop data formats and preprocessing techniques tailored for LLM training and fine-tuning.
- Implement feedback mechanisms to refine data collection and labeling workflows based on quality analysis.
Benefits
- Competitive compensation with salary, equity, and benefits included.
- Flexible collaboration model using asynchronous and synchronous communication, including weekly meetings, Slack, and periodic in-person gatherings.
- Engage in meaningful projects that advance Ethereum's scalability and influence the evolution of cryptocurrency.
- Work in an environment that prioritizes truthfulness, initiative, and collective responsibility toward bold objectives.
- Committed to equal opportunity employment without regard to protected characteristics under applicable laws.
Compensation
Competitive salary + equity + benefits package
Work Arrangement
Remote (Worldwide)
Team
Collaborate across distributed teams with regular digital check-ins and quarterly face-to-face sessions
Responsibilities
- Design and document formal data annotation strategies with scalable labeling guidelines and quality metrics such as inter-annotator agreement.
- Research and prototype data formats, structures, and preprocessing methods optimized for LLM training and fine-tuning.
- Develop automated systems to evaluate the quality of raw and annotated data, feeding insights back into workflow improvements.
- Partner with engineers to shape data processing pipelines and ensure infrastructure supports machine learning requirements.
Not specified
