About the Role
YO IT Consulting is seeking a Geology Quality Assurance Lead for a remote, contract position. This role is critical for overseeing the quality, consistency, and performance of AI training projects focused on geology and earth sciences. The successful candidate will contribute to the accuracy and contextualization of training data used by leading AI companies and foundation-model labs, directly impacting the improvement of premier AI models.
Role Overview and Responsibilities
In this role, you will be responsible for ensuring the high quality of AI-generated earth science and geology content. This involves reviewing AI outputs and the work of trainers and QA personnel against project guidelines. You will provide precise written feedback to contributors, assessing work for scientific accuracy, geologic reasoning, terminology, spatial and temporal context, data interpretation, clarity, formatting, and adherence to project-specific rubrics. Key responsibilities include:
- Evaluating AI-generated content and trainer/QA work for quality and adherence to guidelines.
- Providing detailed written feedback to ensure contributors meet expected quality standards.
- Assessing work for scientific accuracy, geologic reasoning, terminology, context, data interpretation, clarity, and rubric compliance.
- Spot-checking geology and earth science items, identifying quality issues, and delivering ongoing feedback.
- Escalating recurring or critical quality issues.
- Evaluating AI-generated explanations, summaries, process descriptions, and interpretations for accuracy and clarity.
- Flagging any misleading, geologically impossible, unsupported, or poorly contextualized earth science claims.
Communication and Support
Effective communication is essential for this role. You will be responsible for:
- Communicating project updates, new guidelines, workflow changes, and quality expectations to trainers and QAs via platforms like Discord.
- Promptly responding to questions from trainers and QAs, particularly concerning geological concepts and rubric interpretation.
- Supporting the onboarding of new contributors.
- Monitoring contributor activity, encouraging engagement, and flagging availability issues when necessary.
Documentation and Process Improvement
This role involves maintaining and improving project documentation and processes:
- Creating and maintaining project documentation, including style guides, trackers, FAQs, quality notes, and onboarding materials.
- Identifying recurring quality issues and proposing workflow enhancements.
- Assisting in the development of scalable QA processes for earth science and geology AI training projects.
Qualifications and Experience
Candidates should possess the following qualifications:
- A Bachelor’s, Master’s, or PhD degree in Geology, Earth Sciences, Geoscience, Environmental Science, Geophysics, Geochemistry, Hydrology, Paleontology, Oceanography, or a closely related field.
- A minimum of 2-5 years of experience in geology/earth science research, teaching, fieldwork, environmental consulting, geospatial analysis, academic review, science communication, or related areas.
- Experience leading or supporting remote teams of researchers, educators, reviewers, or QAs is strongly preferred.
- Experience with AI training, data annotation, LLM evaluation, scientific QA, or rubric-based review is a significant advantage.
Skills and Knowledge
Required skills and knowledge include:
- Strong command of the English language for clear communication and feedback.
- A solid understanding of core geological concepts including plate tectonics, the rock cycle, mineralogy, stratigraphy, geologic time, structural geology, geomorphology, natural hazards, climate systems, hydrology, and earth system processes.
- The ability to critically evaluate earth science content against detailed rubrics and identify specific types of errors.
- Exceptional attention to detail and organizational skills.
- Comfort working in fast-paced remote environments using tools such as Discord, Google Sheets, Google Docs, and project management systems.
- Familiarity with tools or methods such as GIS, remote sensing, geologic mapping, field methods, core/log interpretation, geochemical data, climate datasets, Python/R, or scientific visualization is preferred.
The selection process includes an AI interview, a domain-specific task, and an interview with a recruiter. While there is no immediate project for this role, qualified candidates will be prioritized for future relevant opportunities and gain access to YO IT Consulting's expert network.
/ ساعة
دوام جزئي
