
Chemistry Specialist
1 dia atrás
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 of choice for 4 out of 5 of the world's biggest technology companies, as well as leading companies across financial services, insurance, technology, law, and medicine.
By combining advanced machine learning and artificial intelligence (ML/AI) technologies, a global workforce of subject matter experts, and a high-security infrastructure, we're helping usher in the promise of AI. Innodata offers a powerful combination of both 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're poised for a period of explosive growth over the next few years.
About the Role Key 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 the field of 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 is aligned with industry best practices.
- Stay up to date with the latest advancements in Chemistry and AI to continuously improve training methodologies.
- 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 highly desirable.
- Experience working 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.
- Familiarity with AI, Machine Learning, and Large Language Models (LLMs)
- Experience using annotation tools or content management platforms.
- Basic knowledge of Python or data handling tools (preferred but not mandatory).
- Understanding of data quality control processes.
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