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Environmental AI Training Specialist

Rise Data Labs RiseDataLabs ContractRemote
Posted Oct 3, 2026 · ✓ Still open — checked 5 hours ago

Quick facts

Type
Contract
Location
Remote
Platform
RiseDataLabs — 106 open jobs
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Key Responsibilities

Train and enhance AI models by performing data annotation and labeling specific to environmental science.
Review and validate AI-generated content for accuracy, relevance, and adherence to environmental standards.
Provide domain expertise to enhance AI model performance, ensuring that models reflect current environmental knowledge and practices.
Contribute to a variety of AI training projects across different sectors within environmental science.
Ensure high-quality data for machine learning applications, maintaining rigorous quality assurance standards.
Required Skills and Qualifications
Bachelor’s degree in Environmental Science, Ecology, or a related field.
Strong understanding of environmental science concepts and current trends.
Experience in data annotation, labeling, or similar roles within AI training.
Exceptional attention to detail and accuracy in data handling.
Proficient in using data annotation tools and software.

Preferred Qualifications

Experience working with AI and machine learning technologies.
Familiarity with environmental data sets and regulatory frameworks.
Strong analytical and critical thinking skills.
Excellent communication skills and ability to work collaboratively.
What We Offer
At Rise Data Labs, we value our team members and offer a supportive work environment that fosters growth and innovation. You will have the opportunity to work on diverse projects, collaborate with talented professionals, and contribute to impactful AI solutions in the environmental sector. We also provide competitive compensation, flexible work arrangements, and opportunities for professional development.

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About RiseDataLabs

Rise Data Labs hires AI training specialists to create and review data for language models. Openings cover programming (Python, JavaScript, C#, SQL, HTML), chemistry, finance, data annotation and non-English languages such as French.