Descripción de la oferta
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: At Innodata, we’re working with the world’s largest technology companies on the next generation of generative AI and large language models (LLMs). We’re looking for smart, savvy, and curious subject matter experts. We are seeking a highly skilled and motivated Chemistry Subject Matter Expert (SME) to contribute to the development and training of AI Large Language Models (LLMs). As a Chemistry SME, you will play a critical role in guiding AI models to understand complex chemistry concepts, ensuring accuracy, relevance, and contextual understanding in the domain. 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. Key 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,polymer chemistry,radiation chemistry 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. Technical Skills (Preferred): 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. As part of the project, you are required to complete the English language assessment. *The assessment is mandatory & non-billable* If interested, kindly share your updated resume at : tsingh3@innodata.com
