Innodata (NASDAQ: INOD) is a leading data engineering company. With more than 2,000 customers and operations in 13 cities around the world, we are an AI technology solutions provider for major technology companies and other industries, helping usher in the promise of AI. Innodata offers a powerful combination of digital data solutions and easy-to-use, high-quality platforms. Our global workforce includes over 5,000 employees in the United States, Canada, United Kingdom, the Philippines, India, Sri Lanka, Israel and Germany. We are poised for growth.
About the Role
At Innodata, we are working with the world7s largest technology companies on the next generation of generative AI and large language models (LLMs). We are seeking a highly skilled Chemistry Subject Matter Expert (SME) to contribute to the development and training of AI Large Language Models (LLMs). As a Chemistry SME, you will guide AI models to understand complex chemistry concepts, ensuring accuracy, relevance, and contextual understanding in the domain.
Responsibilities
Collaborate with AI researchers, data scientists, and engineers to train, refine, and evaluate Large Language Models with a focus on Chemistry content.
Develop high-quality, accurate, and domain-specific datasets, including conceptual explanations, technical documents, research abstracts, and problem-solving content.
Review and validate AI-generated content for technical accuracy, clarity, and contextual relevance in Chemistry.
Provide expert feedback on model outputs, identify conceptual gaps, and suggest improvements to enhance model learning.
Assist in creating and annotating training datasets, including classification, tagging, and contextual labeling of chemistry-related data.
Ensure all content meets scientific rigor and aligns with industry best practices.
Stay up to date with the latest advancements in Chemistry and AI to continuously improve training methodologies.
As part of the project, complete the English language assessment.
Qualifications
Master's or PhD in Chemistry, Chemical Engineering, or related scientific field.
Strong theoretical and practical knowledge of chemistry concepts (Organic, Inorganic, Physical, Analytical, Biochemistry, etc.).
Prior experience in academic research, technical writing, or teaching is desirable.
Experience with data annotation, content development, or training AI models is a plus.
Excellent written and verbal communication skills in English.
Strong analytical and problem-solving skills; detail-oriented with a passion for accuracy and scientific precision.
Technical Skills (Preferred): Familiarity with AI/ML/LLMs; experience using annotation tools or content management platforms; basic knowledge of Python or data handling tools.
Understanding of data quality control processes.
Other Details
The English language assessment is mandatory and non-billable.
Seniority level
Entry level
Employment type
Full-time
Job function
Research, Analyst, and Information Technology
Industries
Business Consulting and Services
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